TWI586180B - An image processing apparatus, an image processing method, and a storage medium for storing a program - Google Patents

Description

Image processing device, image processing method, and storage medium for storing programs

The present invention relates to an image processing apparatus for processing an image.

In the prior art, there has been an interpolating device for digital image signals characterized by the following devices. The digital image signal interpolation device includes: means for receiving input image data, and extracting a predetermined number of pixel data existing at a peripheral position of the predetermined pixel; and using pixel data required for obtaining the coefficient, Predetermining a predetermined number of coefficients by a minimum self-multiplication method in a manner of maximizing the error of the interpolated value and the true value, and a linear combination of the extracted predetermined number of pixel data, and interpolating the predetermined order A device for displaying pixel data (see Patent Document 1).

Further, there is also a digital video signal conversion device that generates a second digital video signal having a larger number of pixels than the first digital video signal from the first digital video signal (see Patent Document 2).

[Previous Technical Literature]

(Patent Document 1) Japanese Patent No. 2825882 (page 1, page 1, etc.)

(Patent Document 2) Japanese Patent No. 3072306 (first page, first figure, etc.)

However, conventional techniques cannot output images that adjust brain load depending on the purpose.

An image processing device according to a first aspect of the present invention includes: a storage unit that stores a lookup table having one or two or more pieces of corresponding information, wherein the corresponding information is used to acquire one or two or more first images. All or part of the information corresponding to all or a part of the second image, and the second image is compared with the first image, and the brain load is adjusted and the same object as the first image The image receiving unit receives one or two or more images, and the mapping unit acquires one or more accepted by the image receiving unit using one or more of the corresponding information. All or part of one or two or more second images corresponding to all or a part of the image; and an image output unit that outputs all of the one or more second images obtained by the mapping unit or is a mapping unit One or more output images of a set of one or more of the acquired second images.

According to this configuration, it is possible to output an image in which the brain load is adjusted according to the purpose.

Further, in the image processing device according to the second aspect of the present invention, in the first aspect of the invention, the lookup table has two or more pieces of corresponding information, and is provided with one or more images for determining the image receiving unit. An image analysis unit that includes all or a part of the first image corresponding to all or a part of the first image; and the mapping unit uses the corresponding information corresponding to all or a part of the first image determined by the image analysis unit to obtain and A second image corresponding to all or a part of the first image determined by the image analysis unit.

According to this configuration, it is possible to output an image in which the brain load is adjusted according to the purpose.

Furthermore, in the image processing apparatus of the third invention of the present application, all or part of the first image is a first space-time block of a part of the input image, and the second image is All or part of the image is a second space-time block that is output to one of the images of the screen; the image receiving unit receives the image of the set of one or more images, and includes a dividing unit for accepting the image receiving unit The image is divided into two or more spatially, temporally, spatially, temporally, and temporally, and two or more first space-time blocks are obtained; and the image analysis unit acquires two or more pieces according to the division unit. Each of the time-space blocks determines all or a portion of the first image corresponding to each of the first space-time blocks; the mapping portion further has a synthesis portion, whereby each of the two or more first space-time blocks And acquiring, by using the correspondence information corresponding to all or a part of the first image determined by the image analysis unit, the second spatiotemporal block corresponding to all or a part of the first image determined by the image analysis unit And obtained by the mapping department The two or more second spatiotemporal blocks are arranged in temporal, or spatial, or spatial and temporal positions of the first spatiotemporal block corresponding to the two or more second spatiotemporal blocks, and generate an output image. The image output unit outputs the output image generated by the synthesizing unit.

According to this configuration, it is possible to output an image in which the brain load is adjusted according to the purpose.

Further, in the image processing device according to the fourth aspect of the present invention, the image analysis unit obtains one or more images received by the image receiving unit or the divided portion. The two or more first spatiotemporal blocks are analyzed, and one or more feature quantities are acquired, and all or a part of the first image corresponding to one or more feature amounts is determined.

According to this configuration, it is possible to output an image in which the brain load is adjusted according to the purpose.

Further, in the image processing device according to a fifth invention of the present invention, in relation to any one of the first to fourth inventions, the corresponding information has all or a part of the first image of an object obtained in an environment. One or more feature quantities; and a set of parameters used to generate all or a portion of the second image corresponding to all or a portion of the first image, or a set of parameters substituted into the formula.

According to this configuration, it is possible to output an image in which the brain load is adjusted according to the purpose.

Further, in the image processing device according to the sixth aspect of the present invention, in the first to fifth inventions, the storage unit stores two or more pairs of the type identifiers for identifying the types of the lookup tables and a pair of lookup tables corresponding to the type identifier; the mapping unit includes: a type identifier acquiring means for acquiring a type identifier for identifying a type of the lookup table to be used; and an output image obtaining means for using All or a part of the second image corresponding to all or a part of the image accepted by the image receiving unit is obtained as any one of the corresponding information of the lookup table corresponding to the type identifier, and Output all or part of the image.

According to this configuration, it is possible to output an image in which the brain load is more appropriately adjusted depending on the purpose.

Further, in the image processing device according to the seventh aspect of the present invention, the invention of any one of the first to sixth invention further includes: an instruction accepting unit that receives an instruction from the user; and a lookup table update unit that follows The instruction changes any one of the two or more corresponding information that the lookup table has.

According to this configuration, it is possible to output an image in which the brain load is more appropriately adjusted depending on the purpose.

Further, in the image processing device according to the eighth aspect of the present invention, the invention of any one of the first to seventh invention includes a restriction condition (beaming condition) storage unit that is stored as an input image, corresponding information, or The restriction condition for the condition that one or more kinds of information in the output image should satisfy the condition; the mapping unit uses one or more corresponding information of one or more corresponding information to conform to the restriction condition, All or part of one or more second images corresponding to all or a part of one or more images accepted by the image receiving unit is obtained.

According to this configuration, it is possible to output an image in which the brain load is more appropriately adjusted depending on the purpose.

The lookup table acquisition device according to a ninth invention of the present application includes: a first image storage unit that stores one or more first images; and a second image storage unit that stores one or more first images. One or more second images, the second image being an image with adjusted brain load compared to the first image; and a storage portion storing a lookup table having one or more corresponding information, Corresponding information is information for obtaining all or a part of one or more first images and all or a part of one or more second images; the lookup table component is stored in the first image storage unit All or part of one or more first images and all or part of one or more second images stored in the second image storage unit to form a lookup table having one or two or more corresponding information; The table storage unit stores the lookup table formed by the lookup table configuration unit in the storage unit.

According to this configuration, it is possible to generate information for outputting an image in which the brain load is adjusted according to the purpose.

In the look-up table obtaining device of the tenth invention of the present invention, the corresponding information includes: first image related information relating to information of all or a part of one or more first images; and For the second image related information of the information corresponding to the information related to the first image, and the second image related information of the information corresponding to the information related to the first image, the lookup table obtaining device further includes: the first image related information The acquisition unit acquires one or more first image related information related to all or a part of information of one or more first images stored in the first image storage unit from all or a part of the one or more first images. And the second image related information acquisition unit acquires information on all or a part of the one or more second images stored in the second image storage unit from all or part of the one or more second images. More than one second image related information; the lookup table forming unit is configured to form a lookup table having one or two or more corresponding information, the corresponding information having: the first image obtained by the first image related information obtaining unit Related And the second image related information obtained by the second image related information obtaining unit corresponding to the first image related information, and the corresponding information is all or part of displaying one or more first images Information corresponding to all or a portion of one or more second images.

According to this configuration, it is possible to generate information for outputting an image in which the brain load is adjusted according to the purpose.

Further, in the lookup table acquisition device according to the eleventh aspect of the present invention, the correspondence information includes: a feature amount vector corresponding to all or a part of one or more first images, and Converting all or part of one or more first images into an image conversion filter of all or part of one or more second images; and the lookup table forming part is from one or more first images All or a part of the feature quantity vector is obtained, and a conversion filter that converts all or a part of one or more first images into one or more of the one or more second images is obtained, and one or two or more components are provided. A lookup table of the feature quantity vector and corresponding information of the conversion filter.

According to this configuration, it is possible to generate information for outputting an image in which the brain load is adjusted according to the purpose.

Further, in the lookup table acquisition device (image processing device) according to the twelfth aspect of the present invention, the second image information candidate set storage unit is provided with one storage device and one for the ninth to eleventh inventions. One or more second image information candidate sets corresponding to the first images, wherein the second image information candidate set is two or more second image information related to one or more first images The candidate output unit outputs one or more second image information candidate sets, and the instruction accepting unit accepts two of the one or more second image information candidate sets outputted from the candidate output unit. An instruction to select one or more second image information candidates in the candidate for the second image information; and a second image storage unit that uses one or more second maps corresponding to the instruction received by the instruction accepting unit For example, the information candidate is obtained by acquiring one or more second images, and the one or more second images are stored in the second image storage corresponding to the first image corresponding to the second image information candidate set. unit.

According to this configuration, information for outputting an image of the adjusted brain load to a specific user can be generated.

According to the image processing apparatus provided by the present invention, it is possible to output an image whose brain load has been further adjusted according to the purpose as compared with the input image.

1, 2, 4, 5, 6‧‧‧ image processing devices

3‧‧‧ lookup table acquisition device

7‧‧‧Image learning device

31‧‧‧First Image Storage Department

32‧‧‧Second image storage

33‧‧‧Second image information candidate collection storage unit

34‧‧‧ alternate output

35‧‧‧Second image storage

36‧‧‧First Image Related Information Acquisition Department

37‧‧‧Second image related information acquisition department

38‧‧‧ Lookup Table Composition Department

39‧‧‧ Lookup Table

71‧‧‧Image Generation Department

72‧‧‧Image Accumulation Department

101‧‧‧ Storage Department

102, 502‧‧‧Restricted Condition Storage Department

103, 503, 603‧‧‧Directed Reception Department

104‧‧‧Image Reception Department

105‧‧‧ Division

106‧‧‧Image Analysis Department

107, 507, 607‧‧ ‧ mapping department

108‧‧‧Combination Department

109‧‧‧Image Output Department

110‧‧‧ Lookup Table Update Department

340‧‧‧ computer system

341‧‧‧ computer

342‧‧‧ keyboard

343‧‧‧ Mouse

344‧‧‧ display

510‧‧‧Restricted Condition Change Department

610‧‧‧LUT Change Information Change Department

1071‧‧‧Type identifier acquisition device

1072‧‧‧ Output image candidate acquisition device

1073‧‧‧Judgement device

1074, 5074‧‧‧Change device

1075‧‧‧ Output image acquisition device

3411‧‧‧FD drive

3412‧‧‧CD-ROM drive

3413‧‧‧MPU

3414‧‧ ‧ busbar

3415‧‧‧ROM

3416‧‧‧RAM

3417‧‧‧ Hard disk

3501‧‧‧CD-ROM

3502‧‧‧FD

5071‧‧‧Feature quantity acquisition device

5072‧‧‧Restriction determining device

6071‧‧‧First feature quantity acquisition device

6072‧‧‧Second feature quantity acquisition device

6073‧‧‧LUT change information storage device

6074‧‧‧LUT decision device

1 is a block diagram of an image processing apparatus 1 according to Embodiment 1, FIG. 2 is a flowchart for explaining an operation of the image processing apparatus 1, and FIG. 3 is a flowchart for explaining an image analysis processing; The figure is a flow chart for explaining the mapping process; FIG. 5 is a flow chart for explaining the process of obtaining the class identifier; FIG. 6 is a flow chart for explaining the process of updating the lookup table; and FIG. 7 is a flowchart for explaining another image processing device; FIG. 8 is a block diagram of the image processing apparatus 2 of the second embodiment; FIG. 9 is a flowchart for explaining the operation of the image processing apparatus 2; and FIG. 10 is another image processing apparatus 2; FIG. 11 is a block diagram of the lookup table acquisition device 3 of the third embodiment; FIG. 12 is a flow chart for explaining the second image selection operation of the lookup table acquisition device 3; and FIG. 13 is a lookup table. FIG. 14 is a view showing an example of a plurality of second image information candidate sets; and FIG. 15 is a view showing an output example of the second image information candidate set; Figure 16 shows the first image of Embodiment 4. Figure 17 is a diagram showing an example of a second image; Figure 18 is a diagram showing an example of a first space-time block; Figure 19 is a diagram showing an example of a second space-time block; and Figure 20 is a diagram showing an example of a second space-time block; A conceptual diagram of the operation of the table constituent unit; a conceptual diagram of the processing of the lookup table constituent unit in the 21st; and a conceptual diagram of the processing of the lookup table constituent unit in the 22nd.

Fig. 23 is a view showing an example of a lookup table; Fig. 24 is a block diagram showing an image processing apparatus 4 according to the fifth embodiment; Fig. 25 is a view showing an example of an image having a shallow depth of field; and Fig. 26 is a view showing a map portion; Figure 27 is a block diagram of the image processing apparatus 5 of the sixth embodiment; and Fig. 28 is a diagram showing an example of the constraint information; Fig. 29 is a flow chart for explaining the operation of the image processing apparatus 5; Fig. 30 is a flow chart for explaining the mapping processing; Fig. 31 is a flowchart for explaining the restriction condition determining processing; and Fig. 32 is an implementation flowchart; Fig. 33 is a block diagram showing an example of the LUT change information management table; Fig. 34 is a flow chart showing the operation of the image processing apparatus 6; and Fig. 35 is a map processing FIG. 36 is a block diagram showing an LUT decision process; FIG. 37 is a block diagram of the image learning device 7 of the eighth embodiment; and FIG. 38 is an overview of the computer system of the above embodiment; Figure 39 is a block diagram of a computer system.

(Embodiment of the invention)

Hereinafter, embodiments of an image processing apparatus and the like will be described with reference to the drawings. In the embodiment, the same components are denoted by the same reference numerals, and the description thereof will not be repeated.

(Embodiment 1)

In the present embodiment, an image processing apparatus that obtains an image whose brain load is further adjusted according to the purpose of obtaining an image compared to the accepted image is described using a lookup table (LUT) to be described later. Further, the image in which the brain load is adjusted according to the purpose is, for example, an image in which the brain load is further reduced at the time of viewing, or an image in which the brain is stimulated at the time of viewing to add entertainment. An image in which the brain load is further reduced during viewing and viewing is, for example, an image that is easier to recognize. In addition, the purpose is usually for the purpose of viewing the image by the viewer, for example, to relax the purpose of viewing, to listen for a long time, to prevent fatigue, and to enjoy the purpose of entertainment. .

Further, in the present embodiment, the process of obtaining an image for adjusting the brain load according to the purpose is processed in accordance with, for example, each spatiotemporal block. A description of the space-time block is presented later.

Further, in the present embodiment, the lookup table can be customized.

Further, in the present embodiment, the image processing apparatus 1 has a function of performing conversion to satisfy the predetermined condition when the image of the output candidate does not satisfy the predetermined condition.

Fig. 1 is a block diagram showing an image processing apparatus 1 of the present embodiment.

The image processing device 1 includes a storage unit 101, a restriction condition storage unit 102, an instruction reception unit 103, an image reception unit 104, a division unit 105, an image analysis unit 106, a mapping unit 107, a synthesis unit 108, and an image output unit. 109. The lookup table update unit 110.

The mapping unit 107 includes, for example, a type identifier acquiring unit 1071, an output image candidate acquiring unit 1072, a determining unit 1073, a changing unit 1074, and an output image obtaining unit 1075.

The storage unit 101 can store one or two or more lookup tables. The storage unit 101 may also store two sets of pairs of the above-mentioned types of identifiers for identifying the type of the lookup table and the lookup table corresponding to the type identifier. Further, the data structure of the lookup table is not limited to a table type structure. The data structure of the lookup table is not asked. Moreover, the so-called lookup table type can also be the lookup table itself, when there is no need to rumor.

Here, the lookup table has one or more corresponding information. The correspondence information is information for obtaining all or a part of one or two or more first images and all or a part of one or two or more second images. When the corresponding information of the lookup table is one, the corresponding information is, for example, a calculation formula of the converted image or one or more parameter groups to be added to the converted image calculation formula. The corresponding information may also be, for example, a calculation formula for calculating the intermediate value of the pixel values of the spatiotemporal block.

Further, all or a part of the one or more first images and all or a part of the one or more second images may be an image of one picture to be outputted, or may be an image of a part of a block. It can also be a single pixel, or a plurality of pictures that are consecutive in time, or a part of the space of a plurality of pictures that are consecutive in time (the space-time block described later), or a plurality of pictures that are consecutive in time. A collection of consecutive pixels, etc. In other words, the unit of information amount of the first image and the second image is not asked. In addition, the term "space-time block" generally refers to a part of the image obtained by spatial, temporal, or spatial and temporal division. However, the space-time block can be a collection of pixels. In other words, the space-time block is not limited to a continuous area of a rectangle. The space-time block can also be a non-rectangular and discontinuous image area. Moreover, the image obtained by dividing the image A plurality of spatiotemporal blocks may also have partially repeated pixels.

The second image is, for example, an image in which the load on the brain can be further reduced as compared with the first image when viewing is performed. Further, the second image is an image in which the load of the brain is generally reduced as compared with the first image when the object is recognized. The image that can reduce the load on the brain is that the brain can feel texture, distance, presence, presence, weight, warmth, coolness, speed, sensation, smooth movement. An image of one or more attributes in the sense of sex, freshness, and sense of quality. Also, the properties will vary depending on the image. In addition, the texture refers to the texture of the object included in the image such as the texture, the gloss, the transparency, the fluffiness, and the moist feeling. Moreover, the so-called sense of distance can also be said to be a sense of resolution, a sense of three-dimensionality, a sense of depth, and a sense of air.

In addition, the image that can reduce the brain load can also be said to be an image that allows the brain to feel comfortable.

Further, one or more second images that can reduce the brain load compared to one or more first images are, for example, one or more images acquired in an environment different from the one or more first images. . That is, in this case, for example, the environment in which one or more second image acquisition images are different from one or more first images.

The first image is, for example, an image of an object obtained in an environment. Furthermore, the second image is, for example, an image obtained in another environment relating to the aforementioned one object. Further, the first image is, for example, an image obtained by photographing an object in an environment. Further, the second image is, for example, an image obtained by photographing the aforementioned one object in another environment. Furthermore, in this case, the second image and the first image are usually the same number of pixels, but may also be different pixel numbers. In addition, an image obtained by capturing an object may be an image created by shooting an object.

In addition, the other environment is an environment different from an environment, and is an environment in which an image more suitable for an environment can be captured. Moreover, the other environment is, for example, an environment in which an image capable of reducing brain load is more than one environment. Further, the other environment may be, for example, an environment like the following (1) to (9). (1) The illumination (light source) has more light than an environment, and (2) compared with an environment, the position of the light source can clearly show the environment of the shadow of the object on the image, and (3) compared with an environment. The position of the light source can clearly show the environment of the three-dimensionality of the object on the image, and (4) the position of the camera can be clearly displayed compared with an environment. The environment in which the object is three-dimensional, (5) the environment in which the lighting color is different from the environment, (6) the environment in which the weather is different from the environment, (7) the environment in which the temperature or humidity is different from the environment, and (8) the depth of field. An environment different from an environment, (9) a shutter speed and an environment different from the environment.

That is, the shooting environment is different for one environment and another environment, such as the amount of light, the position of the light source, the color of the light source, the position of the camera, the setting of the camera, and the like. In addition, the environment generally refers to a shooting environment, but any environment may be used as long as it has an environment for acquiring images.

In addition, the second image does not include an image having only a larger number of pixels than the first image. Such an image having only a large number of pixels is simply a picture taken by a camera having a large number of pixels (for example, an HD camera) as a standard image. On the other hand, the present invention is suitable for The image of the brain is determined by the judgment of the brain and the way of feeling of the brain (also known as the way of feeling of the human being) as a standard image, which is separated by a line.

The second image of the adjusted brain load relative to the first image also includes, for example, an image that is more entertaining than the first image. An entertaining image is an image that is suitable for entertaining users and is suitable for the brain to feel. An image suitable for the brain to feel is also called an image in which the brain can enjoy stimulation. Moreover, the plurality of images (images) that are improved in entertainment are, for example, images in which a flashing picture (flash picture such as a flash shot) is partially inserted.

In addition, if the second image of the adjusted brain load is an image that is more entertaining than the first image, the second image can make the brain more stimulating, but also has a brain. The load is even more complicated.

Furthermore, the second image that adjusts the brain load according to the purpose compared to the first image is, for example, an image obtained by deforming the first image with respect to the first image obtained by capturing an object. . The second image obtained by deforming the first image is, for example, a portrait image of a person who takes in the first image. An image obtained by deforming a portrait image or the like is easy for the user to recognize the object, and can be said to be an image that is adjusted in such a manner that the brain load is reduced when the subject is recognized.

Further, the second image in which the brain load is adjusted according to the purpose is compared with the first image, for example, a picture obtained by drawing a picture depicting the same object with respect to the first image obtained by photographing one object. image. By describing the object, the concept of the object is easy to understand. In other words, an image in which a painting of a subject is photographed is compared with an image obtained by directly photographing a subject, and is an image that adjusts the brain load to reduce brain load.

Meanwhile, the second image that adjusts the brain load according to the purpose compared to the first image is, for example, a CG image of the first image with respect to the first image obtained by photographing one object. Depending on the subject, the CG image can be said to be an image that adjusts the brain load to reduce brain load compared to the captured image.

Moreover, the correspondence information is, for example, a pair of the first image related information and the second image related information. The first image related information is information about all or a part of one or more first images. The second image related information is information about all or a part of one or more second images. The first image related information is, for example, one or more feature quantities extracted from all or part of one or more first images. Further, the second image related information is, for example, all or a part of one or more second images. Further, the second image related information is, for example, a calculation formula that generates all or a part of one or more second images. At the same time, the second image related information is, for example, a parameter group pair placed into a calculation formula for generating all or a part of one or more second images. In this case, the calculation formula is held by the mapping unit 107. Further, among the one or more feature quantities extracted from the image, for example, a near feature quantity of one feature number of one or more images and an overall feature quantity of a feature quantity of one or more images as a whole are included. The near 傍 feature quantity has, for example, a pixel value, an activity value, a temporal space correlation, a motion vector, a frequency distribution, and the like. Further, the activity value is, for example, a maximum value and a minimum value of a plurality of pixels, a dynamic range (DR), a difference value between a plurality of pixels, and the like. The difference between a plurality of pixels can be the difference between the complex pixels in the space, or the difference between the complex pixels in the time direction, or between the complex pixels in the space and in the time direction. Differential value. Further, the overall feature amount is, for example, a pixel value distribution of the entire image, a motion vector distribution of the entire image, a temporal spatial correlation of one or more images as a whole, a noise amount of the entire image, and an image format. Information about the editing of the entire image (whether it is PinP, whether it is PoutP, whether or not there is a subtitle, etc.), content information about the content of one or more images, and pattern detection results (faces, etc.). Here, the content information is, for example, a type, a title, an actor name, and the like of a program included in an electronic program guide (EPG). Further, one or more feature amount weights are also referred to as feature quantity vectors.

Although the storage unit 101 is preferably a non-volatile storage medium, it can also be realized by a volatile storage medium. In particular, the storage unit 101 is preferably a non-volatile RAM. Further, the process of storing the lookup table in the storage section 101 is not a question. For example, the lookup table can be stored by the storage medium. In the storage unit 101, a lookup table transmitted via a communication line or the like may be stored in the storage unit 101, or a lookup table input by the input device may be stored in the storage unit 101.

The restriction condition storage unit 102 can store the restriction condition. The restriction condition is a condition relating to any processing of the image processing apparatus 1. The conditions relating to the processing are, for example, conditions for all or one part of the image (input image) to be processed. Further, the condition regarding the processing is, for example, a condition relating to a lookup table used for processing. Further, the condition regarding the processing is, for example, a condition relating to an output image. The so-called restriction condition can be said to be a condition that one or more kinds of information in the input image, the corresponding information, or the output image should satisfy. In addition, the condition of all or one part of the image (input image) to be processed is a condition in which one or more feature quantities (for example, luminance, pixel value, and the like) of the processing target are used as parameters. The condition with respect to all or a part of the input image means that, for example, the pixel value does not escape the normal range. In addition, the normal range of pixel values is stored in advance. Further, the condition for referring to the lookup table is, for example, a selection condition regarding the selection frequency of the corresponding information of the lookup table or the like. The condition for the lookup table means, for example, that the same information as the corresponding information that has just been used is not used. Meanwhile, the condition regarding the lookup table refers to, for example, a case where the same corresponding information is continuously used under the first specific condition, a case where the specific corresponding information is fixedly used under the second specific condition, and the same correspondence is discontinuously used under the third specific condition. The situation of the information, the case where the specific corresponding information is not used under the fourth specific condition, and the like. Further, for example, the condition for outputting an image is a condition in which one or more feature quantities (for example, luminance, pixel value, and the like) of the output image are used as parameters. The condition regarding the output image can be said to be a constraint condition that all or a part of one or more second images acquired by the mapping unit 107 should satisfy. The condition regarding the output image is, for example, the case where the activity value is within the median value. Further, the condition for outputting the image is, for example, the maximum value of the pixel "the value of the pixel <= 255", the minimum value of the pixel "pixel value>=10", and the change of the pixel value △" The temporal change of pixel brightness is <=100", and the dynamic range is "DR<=200". Restrictions can also be embedded in the program that performs image processing, and there is no doubt about it.

Further, the restriction condition may include two or more conditions in terms of conditions of all or a part of the input image, conditions of the lookup table, and conditions regarding the output image. Such a constraint is such as the case where the difference between the pixel value of the input image and the pixel value of the output image is greater than the threshold value. In addition, the threshold is stored in advance.

The restriction storage unit 102 is preferably a non-volatile storage medium. It can also be implemented with a volatile storage medium. The process of storing the restriction condition in the restriction condition storage unit 102 is not a question. For example, the restriction condition may be stored in the restriction condition storage unit 102 by the storage medium, the restriction condition transmitted by the communication line or the like may be stored in the restriction condition storage unit 102, or the restriction condition input by the input device may be stored in the restriction condition. The storage unit 102.

The instruction accepting unit 103 accepts the instruction. The indication can be received from the user, read from an external storage medium, or received from an external device. Moreover, the indication can also be embedded in the broadcast signal transmitted from the broadcaster. In addition, the indication is an instruction to change the lookup table to suit the user's preference or the like. The indication includes, for example, the degree of stereoscopicity of the image. Further, the instruction is, for example, an instruction to select one or more candidates for the second image from the candidates of the two or more second images included in the one or more second image information candidate sets being output. This choice is an indication of an image that matches the user's preferences. At the same time, the indication may also include user attributes such as age or age (30 generations, 60 generations, etc.), gender, presence or absence of myopia, or presbyopia-disorder adjustment. Further, the indication is, for example, an object or a subject or a preference. For the purpose or subject or preference, there are examples such as "I don't want to see the image, so I hope I can see it more clearly", "The image is too dark, I don't want to see it", "I hope to see a better picture". In summary, the instructions can have a variety of content or categories.

Secondly, it accepts reception of information input by an input device such as a remote controller or a keyboard, a mouse, a touch panel, etc., reception of information transmitted via a wired or wireless communication line, storage from a disc or a magnetic disk, a semiconductor memory, or the like. The concept of acceptance of information read by the media. The input device of the indication may be any one of a remote control or a nine-square grid or a keyboard or a mouse or a menu screen. The instruction accepting unit 103 can be realized by a device driver of an input device such as a digital keyboard or a keyboard, a control software for a menu screen, or the like.

The image receiving unit 104 accepts an image. At the same time, the image receiving unit 104 can accept an image of a set of one or more images. Here, the image may be a static picture or an animation composed of two or more still pictures. The image accepting unit 104 can be realized by, for example, a television tuner or a wireless or wired receiving device. Further, the image reception can also read an image or the like from the storage medium. That is, regardless of the device that accepts the image.

The division unit 105 divides the image (still image or animation) accepted by the image reception unit 104 into two or more depending on the spatiality, temporality, spatiality, and temporality to obtain two images. The first time and space block above. Further, as described above, the plurality of spatiotemporal blocks obtained by dividing the image may also include repeated regions. Moreover, as described above, the plurality of spatiotemporal blocks obtained by dividing the image are not limited to the continuous region of the rectangle. Space-time blocks can also be areas of non-rectangular and discontinuous images. Further, the division unit 105 may divide, for example, one screen (one map field or one frame, that is, a frame frame) into four, or may divide n screens (n is an integer of two or more) into eight. In addition, the number of divisions is not what is asked. Furthermore, the division unit 105 can also acquire pixels from the image one by one and pass it to the image analysis unit 106. That is, the space-time block can also be 1 pixel.

The dividing unit 105 can be generally realized by an MPU, a memory, or the like. The processing program of the dividing unit 105 is usually implemented by software, and the soft system is stored in a storage medium such as a ROM. But it can also be implemented with hardware (dedicated circuit).

The image analysis unit 106 is configured to determine all or part of the first image corresponding to all or a part of one or more images accepted by the image receiving unit 104. For example, the image analysis unit 106 may determine all or part of the first image corresponding to each of the first spatiotemporal blocks in accordance with each of the two or more first spatiotemporal blocks acquired by the dividing unit 105. Further, the image analysis unit 106 may determine all or part of the two or more first images.

In addition, for example, the image analysis unit 106 analyzes the image received by the image accepting unit 104 or the two or more first spatiotemporal blocks acquired by the dividing unit 105, and acquires one or more feature quantities. And determining all or a part of the first image corresponding to one or more feature quantities. Here, the one or more feature amounts are, for example, one or more feature amounts of the above-described near-characteristic feature amount and overall feature amount. In addition, the image analysis unit 106 may analyze only one or more of the one or more images accepted by the image receiving unit 104 to acquire one or more feature amounts. Further, it is preferable that the feature amount obtained by the image analysis unit 106 includes both the total feature amount and the near feature value.

Further, the process of determining all or a part of the first image corresponding to one or more feature amounts is, for example, calculating the acquired feature amount vector and all or a part of the first image of each corresponding information. The distance of the feature quantity vector is a process of obtaining a parameter group, a calculation formula, or the like corresponding to the feature quantity vector of all or a part of the first image having the smallest distance.

Further, the process of determining all or a part of the first image corresponding to one or more feature amounts is, for example, a process of calculating a lookup table address from the acquired feature amount vector. In addition, The process of calculating the lookup table address is a process of substituting the feature quantity vector into a pre-stored calculation formula for calculation.

The image analysis unit 106 can be generally realized by an MPU, a memory, or the like. The processing program of the image analysis unit 106 can be realized by software, and the soft system is stored in a storage medium such as a ROM. However, it can also be implemented by hardware (dedicated circuit).

The mapping unit 107 acquires one or more corresponding to all or a part of one or more images accepted by the image receiving unit 104 by using one of the one or more pieces of corresponding information in the lookup table. All or part of the second image. At the same time, for example, the mapping unit 107 obtains the corresponding information corresponding to all or a part of the first image determined by the image analyzing unit 106 (including the case where one part of the corresponding information (for example, a parameter group) is used). All or part of the second image corresponding to all or a part of the first image determined by the image analysis unit 106 is used as all or part of the output image. The mapping unit 107 acquires, for example, a parameter group of a calculation formula to be included in the corresponding information corresponding to all or a part of the first image determined by the image analysis unit 106, and performs calculation to generate an image analysis unit. All or a portion of the second image corresponding to all or a portion of the first image determined by 106. Further, the mapping unit 107 acquires all or a part of the second image included in the correspondence information corresponding to all or a part of the first image determined by the image analyzing unit 106, for example, from the correspondence information.

The mapping unit 107 can also perform one of the first action or the second action. Here, the first operation is to select one or more types of features acquired by the image analyzing unit 106, and to select one or more images accepted by the image receiving unit 104, and the output can be more consistent. The purpose is to adjust the action of one or more corresponding information of the brain load image. In addition, the second operation is to select one or more images accepted by the image receiving unit 104, and to output a lookup table and one or more images for adjusting the brain load more purposefully. The action corresponding to the information.

Next, the mapping unit 107 may acquire all or more of the one or more second images corresponding to all or a part of one or more images accepted by the image accepting unit 104, using the selected one or more pieces of corresponding information. portion.

Furthermore, the mapping unit 107 may perform one of the third operation or the fourth operation. Here, the third operation uses one or more features acquired by the image analysis unit 106. In order to select one or more images accepted by the image receiving unit 104, it is possible to output an operation of adjusting two or more pieces of corresponding information of an image of a brain load more purposefully. In addition, the fourth operation is to select a lookup table and two or more corresponding images that adjust the brain load in a more suitable manner than one or more images accepted by the image receiving unit 104. The action of information.

Next, the mapping unit 107 may acquire all or part of one or more second images using the selected two or more pieces of corresponding information. Further, when all or part of one or more second images are acquired using two or more pieces of corresponding information, the mapping unit 107 may process one or more images accepted by the image accepting unit 104 using two or more pieces of corresponding information. All or part of the result, and the two or more results of the process are combined to obtain all or part of one or more second images. Meanwhile, when all or part of one or more second images are acquired using two or more pieces of corresponding information, the mapping unit 107 may generate new corresponding information using two or more pieces of corresponding information, and obtain the new corresponding information using the corresponding information. All or part of one or more second images. Further, the fusion of the above-mentioned two or more results is, for example, a case where an image is generated using two or more attributes of an image, or an image having an intermediate property of two or more attributes. .

The mapping unit 107 may use corresponding information corresponding to all or a part of the first image determined by the image analyzing unit 106 for each of the two or more first spatiotemporal blocks (including a part of the corresponding information). The situation) to obtain the second space-time block. Further, the second spatiotemporal block is a second spatiotemporal block corresponding to all or a part of the first image determined by the image analyzing unit 106.

Further, the mapping unit 107 acquires, for example, a parameter group of a calculation formula to be included in the correspondence information corresponding to all or a part of the first image determined by the image analysis unit 106, and performs calculation to obtain the map. A second space-time block corresponding to all or a part of the first image determined by the analysis unit 106. Further, the mapping unit 107 acquires, for example, all or a part of the second image included in the corresponding information corresponding to all or a part of the first image determined by the image analyzing unit 106 from the corresponding information (second space-time block) ).

Further, the mapping unit 107 may perform correction processing after acquiring all or a part of the second image. The correction processing is performed by the mapping unit 107 using all or a part of the feature amount of the image accepted by the image accepting unit 104 and all or a part of the first image included in the corresponding information. The feature quantity is used to correct the processing of all or part of the second image. Furthermore, the image obtained by the correction may also be referred to as a second image, and may also be referred to as an output image. In the correction processing, for example, the mapping unit 107 acquires the difference between the feature amount of all or a part of the image received by the image accepting unit 104 and the feature amount of all or a part of the first image included in the corresponding information, and uses the difference. All or part of the second image is corrected by the difference, and all or a part of the output image is more in line with the correction processing of all or part of the image accepted by the image receiving unit 104.

The mapping unit 107 can be generally implemented by an MPU, a memory, or the like. The processing program of the mapping unit 107 is usually implemented by software, which is stored in a storage medium such as a ROM. But it can also be implemented with hardware (dedicated circuit).

Hereinafter, the case where the mapping unit 107 includes the type identifier acquiring means 1071, the output image candidate obtaining means 1072, the determining means 1073, the changing means 1074, and the output image obtaining means 1075 will be described. Further, the mapping unit 107 does not include the case where the type identifier acquiring means 1071, the output image candidate obtaining means 1072, the determining means 1073, the changing means 1074, and the output image obtaining means 1075 are not provided.

The type identifier acquiring means 1071 constituting the mapping unit 107 acquires one or two or more types of identifiers for identifying the type of the lookup table to be used. When the type identifier acquiring means 1071 associates the type identifier with one or more feature amounts of all or part of the image and stores it in the storage unit 101, it is possible to acquire all of the images accepted by the image accepting unit 104 or One or more feature amounts are determined, and one or more feature amounts closest to the one or more feature amounts are determined, and the type identifier corresponding to the one or more feature amounts is acquired from the storage unit 101. Further, the type identifier acquiring means 1071 may use the type of the program (output program) included in the EPG (Electronic Program Table) stored in the EPG storage unit (not shown) as the type identifier. Further, the type identifier acquiring means 1071 may store the type identifier accepted by the user in a storage medium (not shown) and acquire the type identifier. Further, the type identifier acquiring means 1071 acquires, for example, one or more types of identifiers corresponding to the instructions accepted by the instruction accepting unit 103. For example, when the instruction accepting unit 103 accepts the purpose corresponding to "the image is not easily seen, it is desirable to see it more clearly", the type identifier acquiring means 1071 can obtain the type identification of the type of the lookup table for identifying the noise reduction. Further, for example, the instruction accepting unit 103 accepts the object identifier obtaining means for the purpose corresponding to "the image is not easily seen because it is not easy to see," In 1071, a type identifier for identifying the type of the lookup table that brightens the lighting environment can be obtained. Further, for example, when the instruction accepting unit 103 accepts the object corresponding to "the image is not easily seen, it is desirable to see it more clearly", the type identifier acquiring means 1071 can obtain the type identifier of the lookup table for reducing the noise. And the type identifier of the lookup table that brightens the lighting environment.

In addition, for example, when the instruction accepting unit 103 accepts the object corresponding to "the image is not easily seen, it is desirable to see it more clearly", the type identifier acquiring means 1071 detects the noise in the image and checks it. Know if there is any noise above the threshold. When it is determined that there is a noise equal to or greater than the threshold, the type identifier of the lookup table for reducing the noise is obtained. Further, for example, when the instruction accepting unit 103 accepts the purpose corresponding to "the image is not easily seen, it is desirable to see it more clearly", the type identifier acquiring means 1071 obtains the distribution of the image luminance values. When it is determined that the luminance distribution of the image is dark enough to satisfy the predetermined condition, the type identifier of the lookup table for brightening the illumination environment may be obtained.

The type identifier obtaining means 1071 can be generally realized by an MPU, a memory or the like. The processing program of the type identifier obtaining means 1071 is usually implemented by software, and the software is stored in a storage medium such as a ROM. However, it can also be implemented by hardware (dedicated circuit).

The output image candidate acquisition means 1072 uses the corresponding information corresponding to all or a part of the first image determined by the image analysis unit 106 (that is, may be part of the corresponding information), and obtains and analyzes the image. The first image determined by the portion 106 has all or a portion of the second image corresponding to all or a portion of the first image. Here, all or part of the acquired second image is a candidate for all or part of the output image. In addition, "acquiring all or part of the second image" means using, for example, a set of parameters to be substituted into the calculation formula of the corresponding information or the calculation formula of the corresponding information, and performing calculation to obtain the first The case of all or part of the two images. In this case, the corresponding information has a set of equations required to generate all or a portion of the second image corresponding to all or a portion of the first image, or a set of parameters to be substituted into the formula. Meanwhile, the "acquiring all or part of the second image" may be, for example, acquiring the second image of the corresponding information included in all or a part of the first image determined by the image analyzing unit 106. All or part of the situation.

The output image candidate acquisition device 1072 can be generally realized by an MPU, a memory, or the like. The processing program of the image candidate acquisition device 1072 is usually implemented by software, and the software is stored in a storage medium such as a ROM. However, it can also be implemented by a hardware (dedicated circuit).

The judging means 1073 judges whether or not the restriction condition is satisfied. When the restriction condition is a condition of all or a part of the image to be processed, the determination device 1073 acquires one or more feature amounts of all or a part of the image accepted by the image reception unit 104, and determines one or more pieces. Whether the feature quantity satisfies the constraint. Further, when the restriction condition is a condition relating to the lookup table, the judging means 1073 obtains information on the past use of the lookup table (corresponding to the use history of the condition) to judge whether or not the use history record satisfies the restriction condition. Further, the usage history is, for example, a type identifier of a lookup table used in a process of defining the last n fields (n is an integer of 1 or more) in the input image, or the last n pictures in the input image. The information of the corresponding information used for the processing of the field (n is an integer of 1 or more). Further, when the restriction condition includes the usage history, the usage history is defined as a storage medium that is assumed to be accumulated and generated by the mapping unit 107. In addition, when the condition is that the condition of the image is output, the determination means 1073 performs, for example, whether or not all or a part of the second image acquired by the output image candidate acquisition means 1072 satisfies the restriction condition of the restriction condition storage unit 102. Judge. For example, the determining means 1073 obtains an attribute value (for example, a maximum value of the pixel and a temporal change of the pixel brightness) of all or a part of the second image included in the restriction condition to determine whether the attribute value satisfies the restriction condition ( For example, "Picture 5 maximum <= 255", "Time change of pixel brightness <= 100").

The judging means 1073 can usually be realized by an MPU or a memory or the like. The processing program of the judging device 1073 is usually implemented by software, and the soft system is stored in a storage medium such as a ROM. However, it can also be implemented by hardware (dedicated circuit).

When the judging means 1073 determines that the restriction condition is not satisfied, the changing means 1074 changes all or part of the second image. Further, when the determination means 1073 determines that the restriction condition is not satisfied, the change means 1074 may change the lookup table.

When the determination means 1073 determines that the restriction condition is not satisfied, the changing means 1074 may determine the input image accepted after the determination, or the space-time block obtained after the determination, or one of the input images accepted after the determination. The above feature amount or one or more feature amounts of the space-time block obtained after the determination is changed to satisfy the restriction condition.

When the determination device 1073 determines that the restriction condition is not satisfied, the changing device 1074 changes the image to the extent that the second image of the determination target of the determination device 1073 is satisfied, for example, and acquires the changed image. Here, the "processing to change the condition to satisfy the restriction condition" is, for example, that the maximum value of the plurality of pixels constituting all or part of the second image satisfies the restriction condition (for example, "maximum value <= 255") In a manner, for example, the maximum number of pixels of the plurality of pixels is 255, and the plurality of pixel values are processed as a whole. In addition, the so-called holistic compression of a plurality of pixel values can be used to reduce the number of pixel values by the same ratio, or to reduce the number of pixel values according to different ratios or values.

The changing device 1074 can be generally implemented by an MPU, a memory, or the like. The processing program of the changing device 1074 is usually implemented by software, which is stored in a storage medium such as a ROM, but can also be implemented by a hardware (dedicated circuit).

The output image acquisition device 1075 uses corresponding information corresponding to all or a part of the first image determined by the image analysis unit 106 among a plurality of pieces of corresponding information (mainly: may also be part of the corresponding information) All or part of the second image corresponding to all or a part of the first image determined by the image analysis unit 106 is obtained as all or part of the output image. Here, the above-mentioned plural correspondence information is a plurality of correspondence information of one lookup table of the storage unit 101 or plural numbers of one or two or more lookup tables corresponding to one or two or more types of identifiers. Corresponding information.

Further, the output image acquisition device 1075 preferably obtains: the determination device 1073 determines that all or a part of the second image satisfying the restriction condition, or the changed image acquired by the changing device 1074, or the determination device 1073 determines that the image is satisfied. All or part of the second image of the restriction condition and the changed image obtained by the changing device 1074 are taken as all or part of the output image.

Further, the output image acquisition device 1075 may use one or more pieces of corresponding information included in one or two or more search tables corresponding to one or two or more types of identifiers and the image analysis unit 106. All or a part of one or more second images corresponding to all or a part of one or more images accepted by the image receiving unit 104 is acquired as one or more pieces of corresponding information corresponding to the feature amount, and is used as an output map. Like all or part of it. Further, one or two or more types of identifiers are the type identifiers acquired by the type identifier acquiring means 1071.

Further, the output image obtaining means 1075 is adapted to perform the above-described correction processing.

The output image acquisition device 1075 can be generally implemented by an MPU, a memory, or the like. The processing program of the synthesizing unit 108 is usually implemented by software, which is stored in a storage medium such as a ROM, but can also be implemented by a hardware (dedicated circuit).

The synthesizing unit 108 arranges two or more second spatiotemporal blocks acquired by the mapping unit 107 in a temporal position or a spatial position of the first spatiotemporal block corresponding to the two or more second spatiotemporal blocks, Or spatial and temporal locations and produce an output image.

The synthesizing section 108 can be generally realized by an MPU, a memory, or the like. The processing program of the synthesizing unit 108 is usually implemented by software, and the software is stored in a storage medium such as a ROM, but it can also be realized by a hardware (dedicated circuit).

The image output unit 109 is for outputting an output image. The image output unit 109 can also output an output image generated by the synthesizing unit 108. The term "output" as used herein generally refers to the use of a display of a display and projection using a projector, but also includes the concept of transmitting to an external device or other program.

The image output unit 109 can be thought of as including an output device such as a display or a projector, and can be thought of as not including an output device such as a display or a projector. The image output unit 109 can be realized by, for example, a drive software of an output device, a drive software of an output device, an output device, or the like.

The lookup table update unit 110 changes any one of the two or more pieces of correspondence information included in the lookup table in accordance with an instruction received by the instruction accepting unit 103. The lookup table update unit 110 may update all the corresponding information of the lookup table, and may also update a part of the corresponding information. When the correspondence information includes a calculation formula required to generate all or a part of the second image or a parameter group required to generate all or a part of the second image, the lookup table update unit 110 will include the calculation formula, for example, according to the instruction. The parameter group or the parameter group required to generate all or part of the second image is changed. For example, when the instruction indicates that the degree of stereoscopic effect of the image is included, the lookup table update unit 110 changes the parameter group having the corresponding information by using the degree of stereoscopic feeling of the image input from the user. The method of changing such a situation (the formula required for the change, etc.) is not asked. For example, the lookup table update unit 110 stores the parameter group in a storage medium (not shown) corresponding to the degree of image stereoscopic feeling, and reads the degree of stereoscopic feeling of the image from the storage medium (not shown). The parameter group corresponding to the information. Moreover, for example, the lookup table update unit 110 stores the image stereoscopic effect. The degree of calculation is required for the parameter group of the parameter, and the degree of the stereoscopic effect of the image is substituted into the calculation formula, and the calculation is performed to obtain the parameter group.

In addition, when the instruction accepting unit 103 receives an instruction to select one or more candidates for the second image, for example, the lookup table update unit 110 acquires one or more feature amounts from each of the one or more second images, and acquires The one or more feature quantities are taken as a parameter group. In addition, when the instruction accepting unit 103 receives an instruction to select one or more candidates for the second image, for example, the lookup table update unit 110 acquires one or more feature amounts from each of the one or more second images, and One or more feature quantities are substituted into a pre-stored calculation formula to perform calculation, and a parameter group is obtained.

The lookup table update unit 110 can be generally implemented by an MPU, a memory, or the like. The processing program of the synthesizing unit 108 is usually implemented by software, and the software is stored in a storage medium such as a ROM, but it can also be implemented by a hardware (dedicated circuit).

Next, the operation of the image processing apparatus 1 will be described using the flowchart of FIG.

(Step S201) The image accepting unit 104 determines whether one or more images have been accepted. If one or more images have been accepted, the process proceeds to step S202, and if one or more images are not accepted, the process proceeds to step S210. In addition, the image here is usually an image composed of two or more still pictures.

(Step S202) The dividing unit 105 divides the image accepted in step S201 into two or more spatially or temporally, or spatially and temporally, to obtain two or more first spatiotemporal blocks.

(Step S203) The image analysis unit 106 substitutes 1 for the counter i.

(Step S204) The image analysis unit 106 determines whether or not the i-th block exists in the first spatiotemporal block acquired in step S202. If the i-th block exists, the process goes to step S205, and if the i-th block does not exist, the process goes to step S208.

(Step S205) The image analysis unit 106 performs image analysis processing on the i-th first space-time block. Then, the image analysis unit 106 determines all or a part of the first image corresponding to the i-th first space-time block. The image analysis processing will be described using the flowchart of FIG.

(Step S206) The mapping unit 107 acquires the second map corresponding to all or a part of the first image determined in step S205, using the correspondence information corresponding to all or a part of the first image determined in step S205. All or part of the image, as all or one of the output images section. This type of processing is called mapping processing. The mapping process is explained using the flowchart of FIG. In addition, all or part of the output image obtained in this step is a second space-time block.

(Step S207) The image analysis unit 106 increments the counter i by 1, and returns to step S204.

(Step S208) The synthesizing unit 108 synthesizes the two or more second spatiotemporal blocks acquired in step S206, and generates an output image. More specifically, the two or more second spatiotemporal blocks obtained in step S206 are arranged in time, or spatiality, or in the first spatiotemporal block corresponding to two or more second spatiotemporal blocks. Spatial and temporal position and produce an output image.

(Step S209) The image output unit 109 outputs the output image generated in step S208.

(Step S210) The instruction accepting unit 103 determines whether or not the user's instruction has been accepted. If there is an instruction to accept the user, the process proceeds to step S211, and if the user's instruction is not received, the process returns to step S201.

(Step S211) The lookup table update unit 110 updates the lookup table in accordance with the instruction accepted in step S210. This process is called lookup table update processing. The lookup table update process is described using the flowchart of FIG.

Further, in the flowchart of Fig. 2, the processing is terminated by the interruption of the power supply or the interruption of the processing end.

Furthermore, in the flowchart of FIG. 2, the instruction of step S210 may be accepted in a plurality of images or image streams, and the lookup table may be updated.

Next, the image analysis processing of step S205 will be described using the flowchart of FIG.

(Step S301) The image analysis unit 106 performs image analysis on the i-th first space-time block, and acquires a feature amount vector (referred to as a first feature amount vector) having one or more feature amounts. Further, one or more feature quantities are, for example, one or more feature amounts of the above-described near-minus feature amount and/or overall feature amount. Further, for example, one or more feature quantities mean, for example, a plurality of pixel maximum values (MAX) and minimum values (MIN), a dynamic range (DR=MAX-MIN), a luminance power number distribution, and a difference value in the time direction. Further, the technique for obtaining such one or more feature amounts from an image is a conventional technique, and thus detailed description thereof will be omitted. Further, the feature amount is not limited to the above-described feature amount, and it should be understood.

(Step S302) The image analysis unit 106 substitutes 1 for the counter i.

(Step S303) The image analysis unit 106 determines whether or not the i-th correspondence information exists in the lookup table of the storage unit 101. If the i-th corresponding information exists, the process goes to step S304, and if the i-th corresponding information does not exist, the process goes to step S307. Further, when there are two or more lookup tables in the storage unit 101, any one of the lookup tables can be used in this step. Further, after performing the type identifier acquisition processing described later, a lookup table corresponding to the type identifier obtained by the type identifier acquisition processing can be used.

(Step S304) The image analysis unit 106 acquires a feature amount vector (referred to as a second feature amount vector) included in the i-th correspondence information.

(Step S305) The image analysis unit 106 calculates the distance between the first feature amount vector obtained in step S301 and the second feature amount vector obtained in step S304, and temporarily compares the distance with i (i-th correspondence information). Accumulated in the buffer.

(Step S306) The image analysis unit 106 increments the counter i by 1, and returns to step S303.

(Step S307) The image analysis unit 106 acquires the corresponding information in which the distance stored in the buffer is the smallest. Return to the upper processing. Further, the process of obtaining the corresponding information is a process of determining all or part of the first image.

Further, in the flowchart of FIG. 3, the corresponding information system stores an ID (which may be an address). For example, it may be substituted into a calculation formula in which one or more feature amounts are stored in advance to obtain an ID (may also be a bit). site). That is, the method of image analysis processing is not asked.

Next, an example of mapping processing in step S206 will be described using the flowchart of FIG.

(Step S401) The type identifier acquiring means 1071 constituting the mapping unit 107 acquires the type identifier for identifying the type of the lookup table to be used. An example of such a type identifier acquisition process will be described using the flowchart of FIG.

(Step S402) The output image candidate obtaining means 1072 acquires the parameter group of the corresponding information in the lookup table corresponding to the type identifier acquired in step S401, and the corresponding information is determined by the image analyzing unit 106. Corresponding information corresponding to all or a part of an image.

(Step S403) The output image candidate obtaining means 1072 generates all or a part of the first image determined by the image analyzing unit 106, using the parameter group acquired in step S402. All or part of the corresponding second image. More specifically, for example, the output image candidate acquisition means 1072 substitutes the parameter group acquired in step S402 into the calculation formula stored in advance, and executes the calculation formula. Next, the output image candidate acquisition means 1072 acquires all or part of the second image.

(Step S404) The determination means 1073 reads the restriction condition from the restriction condition storage unit 102.

(Step S405) The judging means 1073 judges whether all or a part of the second image acquired in step S402 satisfies the restriction condition read in step S403, and substitutes the judgment result in the buffer.

(Step S406) If the result of the determination in step S404 is "satisfaction (conformity) restriction condition", the process proceeds to step S407, and if the "not satisfied (disagreement) restriction condition" is reached, the process proceeds to step S408.

(Step S407) The output image obtaining means 1075 obtains all or part of the second image acquired in step S402 as all or part of the output image. Return to the upper processing.

(Step S408) The changing means 1074 changes all or part of the second image acquired in step S402 so as to satisfy the restriction condition, and acquires the changed image.

(Step S409) The output image obtaining means 1075 obtains the changed image obtained in step S408 as all or part of the output image, and returns to the upper processing.

Further, in the flowchart of FIG. 4, a method of generating all or a part of the second image or a method of acquiring all or a part of the second image may be performed by other methods.

Further, in the flowchart of Fig. 4, when the lookup table of the storage unit 101 is one, the processing of step S401 is unnecessary, and it goes without saying.

Next, an example of the type identifier acquisition processing in step S S401 will be described using the flowchart of FIG.

(Step S501) The type identifier acquiring means 1071 acquires the feature amount vector of the i-th block (first image).

(Step S502) The type identifier acquiring means 1071 substitutes 1 for the counter i.

(Step S503) The type identifier acquiring means 1071 determines whether or not the i-th type identifier is present in the storage unit 101. If the i-th type identifier is present, the process proceeds to step S504, and if the i-th type identifier does not exist, the process goes to step S507.

(Step S504) The type identifier acquiring means 1071 acquires the feature amount vector corresponding to the i-th type identifier.

(Step S505) The type identifier acquiring means 1071 calculates the distance between the feature amount vector acquired in step S501 and the feature amount vector acquired in step S504, and temporarily stores it in the buffer in association with the i-th type identifier.

(Step S506) The type identifier acquiring means 1071 increments the counter i by 1, and returns to step S503.

(Step S S507) The type identifier acquiring means 1071 acquires the type identifier corresponding to the minimum distance calculated in step S505. Return to the upper processing.

Further, in the fifth flowchart of the figure, the type identifier acquisition processing may be performed by other methods as described above. That is, in the flowchart of Fig. 5, the type identifier is determined using the feature quantity vector (one or more near feature quantities) of the block. However, as described above, the type identifier may be determined using the overall feature amount or the near feature quantity, the type identifier may be determined using information of the electronic program guide, or the like, or the type identifier may be determined according to an instruction from the user.

Next, the lookup table update processing related to step S211 will be described using the flowchart of FIG.

(Step S601) The lookup table update unit 110 acquires an instruction accepted by the instruction accepting unit 103.

(Step S602) The lookup table update unit 110 acquires one or more parameters included in the instruction acquired in step S601.

(Step S603) The lookup table update unit 110 substitutes 1 for the counter i.

(Step S604) The lookup table update unit 110 determines whether or not the i-th correspondence information exists in the lookup table of the storage unit 101. If the i-th corresponding information exists, the process proceeds to step S605, and if the i-th corresponding information does not exist, the process returns to the upper process.

(Step S605) The lookup table update unit 110 changes the parameter group of the i-th correspondence information or the calculation formula of the i-th correspondence information using one or more parameters acquired in step S602.

(Step S606) The lookup table update unit 110 increments the counter i by 1, and returns to step S604.

Further, in the flowchart of Fig. 6, when there are a plurality of lookup tables, all the lookup tables may be updated.

Next, a specific example of performing dynamic change processing of an image or the like using a restriction condition will be described. By the restriction condition storage unit 102 of the image processing apparatus 1 and the determination means 1073 and the change means 1074 of the mapping unit 107, the image is adjusted so as to satisfy the restriction condition, and the image in which the brain load is adjusted according to the purpose can be output.

The first specific example is a process of correcting the pixel value of the output image when it exceeds a certain value, and converging it to the value. In this case, the restriction condition is "the one or more pixel values of the output image do not exceed the threshold". On the other hand, the changing means 1074 corrects one or more pixels that have been judged by the determining means 1073 to be inconsistent with such a restriction condition so as not to exceed the threshold. Then, the output image acquisition device 1075 uses all or part of the second image determined by the determination device 1073 to satisfy the restriction condition, or the changed image acquired by the changing device 1074, or the determination device 1073 determines that the restriction condition is satisfied. All or part of the second image and the changed image obtained by the changing device 1074 are used to obtain an output image.

The second specific example is a process of performing hole filling correction on the pixel of the input image by using a peripheral pixel when the pixel value of the input image has escaped from the normal range. In this case, the restriction condition refers to the case where the pixel value of the input image does not escape from the normal range. On the other hand, the change device 1074 acquires one or more pixel values of the peripheral pixels of the predetermined range of the pixel, and uses the one or more pixels that have been determined by the determination device 1073 to be inconsistent with such a restriction condition. The above pixel values are used to determine the pixel values of the anomalous pixels. Next, the output image acquisition device 1075 acquires one or more second images by using one or more feature amounts acquired by the changing device 1074 or one or more feature amounts of the image accepted by the image receiving unit 104. a part of.

In the third specific example, when the output image is obtained using the corresponding information, if one of the correspondence information of the lookup table is just used, the processing using the other corresponding information is performed. This situation Next, the restriction condition is "the same correspondence information is not continuously used". The judging means 1073 judges whether or not the corresponding information corresponding to all or a part of the first image determined by the image analyzing unit 106 has just been used. In addition, in such a case, the information used to determine the corresponding information just used is at least temporarily accumulated. Next, when the judging means 1073 determines that the corresponding information corresponding to all or a part of the first image determined by the image analyzing unit 106 is the same as the corresponding information just used, the changing means 1074 obtains the second close correspondence. News. In other words, the changing means 1074 removes all or a part of the determined first image from the image analyzing unit 106, and transmits an instruction for determining all or part of the first image to the image analyzing unit 106 again. The image analysis unit 106 determines all or part of the first image again. The corresponding information corresponding to all or a part of the first image is corresponding information corresponding to all or a part of the first image that is close to the second for the input image or the spatiotemporal block of the processing object. . Then, the output image acquisition device 1075 acquires a part of one or more second images using the correspondence information acquired by the changing device 1074.

The fourth specific example is an example in which the parameters included in the restriction condition are not the same as the object to be changed. The fourth specific example is a case where, for example, when the pixel value of the output image exceeds the threshold value, the specific corresponding information is used for reprocessing. That is, the restriction condition is "the case where one or more pixel values of the output image do not exceed the threshold". Then, the change device 1074 reads the predetermined correspondence information for one or more pixels that have been determined by the determination device 1073 to be inconsistent with such a restriction condition. Using the corresponding information, the output image acquisition means 1075 will again constitute an output image.

The fifth specific example is an example used to determine parameters of a plurality of parts. The fifth specific example is, for example, a case where the difference between the pixel value of the input image and the pixel value of the output image should be within the threshold. The change means 1074 corrects the pixel value of the pixel of the output image, and the pixel value of the pixel of the input image is different from the one or more pixels determined by the determination means 1073 to be inconsistent with the restriction condition. Set within the threshold. The output image obtaining means 1075 obtains an output image of a pixel having such a pixel value.

As described above, according to the present embodiment, it is possible to provide an image processing apparatus for outputting an image in which the brain load is adjusted according to the purpose. For example, according to the present embodiment, it is possible to provide an image processing apparatus for outputting an image whose brain load is more reduced than an input image, or to output an image which is more capable of giving brain stimulation and entertainment. Image processing device, etc.

Further, when the image processing apparatus according to the present embodiment outputs an image in which the brain load is further reduced, the image processing apparatus can output an image that can be recognized as an appropriate image for the human brain.

More specifically, according to the present embodiment, an image that can be recognized as a suitable image for the human brain can be output by outputting an image captured in a different environment such as the amount of light, the position of the light source, the color of the light source, or the position of the camera. More specifically, according to the present embodiment, the brain can be more sensed in texture, proximity, presence, presence, weight, warmth, coolness, speed, sensation, fluency, and freshness. Image of feeling, high sense, etc.

Furthermore, according to the present embodiment, an image whose brain load is adjusted according to the purpose can be output by using an appropriate lookup table in a plurality of lookup tables.

Further, according to the present embodiment, by changing the output image so as to satisfy the restriction condition, it is possible to output an image in which the brain load is more appropriately adjusted according to the purpose.

Meanwhile, according to the present embodiment, by allowing the lookup table to be customized, it is possible to output an image in which the brain load is more appropriately adjusted in accordance with the user's preference or the like.

Further, the image processing device 1 of the present embodiment may be a television receiver. In this case, the image accepted by the image receiving unit 104 is an image constituting a television image.

Further, according to the image processing apparatus 1 of the present embodiment, it is possible to realize an apparatus for generating and outputting an animation for instantly adjusting the brain load according to the purpose of the received animation.

Furthermore, in the present embodiment, when the lookup table has only one correspondence information, the image processing apparatus 1 does not need to include the image analysis unit 106. In this case, the image processing apparatus 1 has a structure as shown in Fig. 7. Further, in this case, the mapping unit 107 acquires one or more second images corresponding to all or a part of one or more images accepted by the image accepting unit 104, using one of the storage unit 101 correspondence information. All or part of it. Further, in this case, the image analysis unit 106 may exist, and the image analysis unit 106 may acquire one or more feature amounts from all or part of the accepted one or more images, and may be used by the mapping unit 107. This feature amount performs the above-described correction processing.

Further, the image processing device 1 of the present embodiment does not need to include a part of constituent elements such as the instruction accepting unit 103 or the lookup table updating unit 110, and it is needless to say.

Further, the processing of this embodiment can also be realized by software. Moreover, the software can be distributed and distributed through software downloading or the like. Alternatively, the software may be stored in a storage medium such as a CD-ROM and distributed. Further, other embodiments in the present specification also correspond to these practices. Further, the software system of the image processing apparatus according to the present embodiment is realized as follows. That is, the program stores a lookup table in the storage medium, the lookup table has one or more corresponding information, and the corresponding information is all or a part of the first image and the second image. Corresponding information is obtained in all or part of the image, and the second image is an image related to the same object as the first image after adjusting the brain load compared to the first image, thereby The image receiving unit receives one or more images, and the mapping unit acquires one or more images accepted by the image receiving unit using any one of the one or two pieces of corresponding information. All or part of one or more second images corresponding to all or part of the image; and the image output unit outputs all of the one or more second images acquired by the mapping unit or obtained by the mapping unit A program that functions as one or more output images of a set of one or more second images.

Further, in the above program, the lookup table preferably has two or more pieces of corresponding information, so that the computer functions as a program for determining the one accepted by the image receiving unit. All or a part of the image corresponds to all or part of the image analysis unit of the first image; and the computer is used as a whole or a part of the first image determined by the image analysis unit. Corresponding to the corresponding information, the map unit that obtains the second image corresponding to all or a part of the first image determined by the image analysis unit functions.

Moreover, in the above program, all or part of the first image is a first space-time block of a part of the image to be input, and all or part of the second image is to be outputted to the image of the screen. a part of the second space-time block, wherein the image receiving unit receives an image of a set of one or more images, and causes the computer to use the image accepted by the image receiving unit in a spatial or temporal manner, or The spatial and temporal division is divided into two or more, and the division unit of the two or more first space-time blocks is further used to function, and the image analysis unit performs two or more first time and space regions obtained by the division unit. Each of the blocks determines all or a part of the first image corresponding to each of the first space-time blocks, and the mapping unit uses the image analysis for each of the two or more first space-time blocks All or part of the first image determined by the Ministry Corresponding to the corresponding information, the second spatiotemporal block corresponding to all or a part of the first image determined by the image analyzing unit is obtained, and two or more second spatiotemporal blocks obtained by the mapping unit are arranged. In the temporal, spatial, or spatial and temporal position of the first spatiotemporal block corresponding to the two or more second spatiotemporal blocks, a synthesis unit that outputs an image is generated to further develop the computer Features.

Further, in the above-described program, the image analyzing unit preferably analyzes one or more images received by the image receiving unit or two or more first time and space blocks acquired by the dividing unit, and obtains A program for causing a computer to function by determining one or more feature amounts to determine all or part of the first image corresponding to the one or more feature amounts.

Further, in the above program, the storage medium stores two sets of pairs of pairs of the lookup table for identifying the type identifier of the lookup table type and the corresponding type identifier, and the mapping unit is provided with The type identifier acquiring means and the output image obtaining means are adapted to cause the computer to function; and the type identifier acquiring means acquires one or more types of identifiers for identifying the type of the lookup table to be used; The image acquisition device uses corresponding information corresponding to all or a part of the first image determined by the image analysis unit from the correspondence information included in one or more lookup tables corresponding to the one or more types of identifiers. All or part of the second image corresponding to all or a part of the first image determined by the image analysis unit is obtained as all or part of the output image.

Further, the program is adapted to cause the computer to be an instruction receiving unit for accepting an instruction from the user, and a lookup table updating unit for changing one of the two or more pieces of corresponding information included in the lookup table in accordance with the instruction. And play the function.

Further, in the software for realizing the image processing apparatus according to the present embodiment, the storage medium stores a lookup table having one or two or more pieces of corresponding information, and the corresponding information is used to acquire one. The information required for the correspondence of all or a part of the first image and all or a part of the second image different from the first image; and the restriction condition is an input image, a corresponding information, or an output image One of the above types of information should satisfy the conditions, and the computer is used as an image receiving unit for accepting one or more images; and the mapping unit uses one or two or more corresponding information to Acquiring all or one or more of the second images corresponding to all or a part of one or more images accepted by the image receiving unit in accordance with the above-described restrictions And a part of the image output unit that outputs an output image composed of all or a part of one or more second images acquired by the mapping unit.

(Embodiment 2)

In the present embodiment, the image processing device 2 does not include the dividing unit 105 and the combining unit 108 as compared with the first embodiment.

Fig. 8 is a block diagram of the image processing device 2 of the embodiment.

The image processing device 2 includes a storage unit 101, a restriction condition storage unit 102, an instruction reception unit 103, an image reception unit 104, an image analysis unit 106, a mapping unit 107, an image output unit 109, and a lookup table update unit 110. .

Next, the operation of the image processing apparatus 2 will be described using the flowchart of FIG. The flowchart of Fig. 9 is a part of the flowchart of Fig. 2. However, the image analysis processing in step S205 is performed on the entire image accepted in step S201. Further, the mapping process of step S206 is also performed for the entire image accepted in step S201.

Furthermore, in the flowchart of Fig. 9, the processing is terminated by the interruption of the power supply or the interruption of the processing.

Further, in the flowchart of FIG. 9, while receiving a plurality of images or image streams, the instruction of step S210 or the update of the lookup table may be accepted.

As described above, according to the present embodiment, it is possible to provide an image processing apparatus for outputting an image in which the brain load is adjusted according to the purpose. For example, according to the present embodiment, it is possible to provide an image processing apparatus that outputs an image that can reduce the brain load compared to the input image, or a map for outputting an image that is more entertaining to the brain. Like a processing device.

Further, when the image processing apparatus according to the present embodiment outputs an image capable of reducing the brain load, the image processing apparatus can provide an image for outputting an image that can be recognized as a suitable image for the human brain. Processing device.

More specifically, according to the present embodiment, it is possible to output an image in which the image is acquired by an image such as an improved light amount, a light source position, a light source color, and a camera position, and it is possible to output an image that the human brain recognizes as appropriate. More specifically, according to this embodiment, the brain can be output I can feel images of texture, distance, presence, sense of presence, weight, warmth, coolness, speed, sensation, smoothness, freshness, and sense of high quality.

Further, a television receiver in which the image processing device 2 of the present embodiment is incorporated may be constructed. In this case, the image accepted by the image receiving unit 104 is an image constituting a television image.

Furthermore, in the present embodiment, when there is only one correspondence information in the lookup table, the image processing device 2 may not include the image analysis unit 106. In this case, the image processing apparatus 1 has the configuration shown in FIG. At this time, the mapping unit 107 acquires all or a part of one or more second images corresponding to all or a part of one or more images accepted by the image accepting unit 104, using one piece of correspondence information of the storage unit 101. In addition, at this time, the image analysis unit 106 stores one or more feature amounts from all or part of one or more images received by the image analysis unit 106, and the map unit 107 can use the feature amount to Perform the above correction process.

Further, the image processing device 2 of the present embodiment does not need to include a partial component such as the instruction accepting unit 103 or the lookup table updating unit 110, and it is needless to say.

Furthermore, the soft system for realizing the image processing apparatus of the present embodiment is a program similar to the one described below. That is, the program stores a lookup table in the storage medium, the lookup table has one or more corresponding information, and the corresponding information is to make all or part of the first image and the second image. Corresponding to all or part of the information required, the second image is an adjusted brain load compared to the first image, and is an image related to the same object as the first image, thereby The computer is an image receiving unit that accepts one or more images, and the mapping unit acquires one or more accepted by the image receiving unit using one of the one or two or more pieces of corresponding information. All or a part of one or more second images corresponding to all or a part of the image; and an image output unit for outputting all of the one or more second images obtained by the mapping unit or the mapping unit A program that functions as one or more output images of a set of one or more second images.

(Embodiment 3)

In the present embodiment, a lookup table acquisition device 3 for generating a lookup table will be described. The lookup table acquisition device 3 is a learning device used to convert all or a part of the first image referred to in the present specification into a lookup table of all or a part of the second image.

Fig. 11 is a block diagram of the lookup table acquisition device 3 of the present embodiment.

The lookup table acquisition device 3 includes a storage unit 101, a first image storage unit 31, a second image storage unit 32, a second image information candidate set storage unit 33, an instruction accepting unit 103, a candidate output unit 34, and a second The image storage unit 35, the first image related information acquisition unit 36, the second image related information acquisition unit 37, the lookup table configuration unit 38, and the lookup table storage unit 39.

The instruction accepting unit 103 accepts an instruction from the user. The indication here is an instruction to output a second image information candidate set stored in the second image information candidate set storage unit 33, an instruction to select one or more second image information candidates, and the like. Here, the user may be a business sponsor who provides the lookup table acquisition device 3, or may be a user (viewer) of the image processing device or the television receiver. In addition, the second image information candidate set and the second image information are described later.

The first image storage unit 31 may store one or more first images. The first image is assumed to be an image to be accepted by the image processing apparatus. The first image is, for example, an image that produces a brain load in the above sense compared to the second image. Further, the first image is, for example, an image that cannot be expected to enhance entertainment.

The first image storage unit 31 is preferably a non-volatile storage medium, but may be realized by a volatile storage medium. The process of storing the first image in the first image storage unit 31 is not a question. The first image of the first image storage unit 31 may also be generated from, for example, the second image of the second image storage unit 32. That is, for example, the brightness of the second image is reduced by a device (not shown), or the simulation of the position of the camera is automatically changed to change the properties of the second image to generate a first image.

The second image storage unit 32 has to store one or more second images. The second image is an image that adjusts the brain load according to the purpose with respect to the first image. For example, the second image is an image that reduces brain load compared to the first image. Further, for example, the second image is an image that has been more entertaining than the first image. Also, for example, the second image is an image taken by capturing an object in another environment.

The second image and the first image are images for the same object. The second image and the first image are usually the same number of pixels, but may also be different pixels.

The second image storage unit 32 is preferably a non-volatile storage medium, but may be implemented by a volatile storage medium. The process of storing the second image in the second image storage unit 32 is not a question. The second image of the second image storage unit 32 may be, for example, the first image from the first image storage unit 31 To produce. That is, for example, the brightness of the first image is increased by a device (not shown), or the simulation of the position of the camera is automatically changed to change the properties of the first image to generate a second image.

The second image information candidate set storage unit 33 can store one or more second image information candidate sets in association with one or more first images. The second image information candidate set is a set of candidates of two or more second image information. The second image information is information about the second image. Furthermore, the second image information may be the second image, or may be one or more attributes of the second image. The attributes of the image are, for example, shooting parameters or one or more feature quantities. In addition, the candidate of the two or more second image information is the first image having the corresponding relationship and the image information of the second image for the same object. The second image information candidate set storage unit 33 may physically include the first image storage unit 31. Meanwhile, the phrase "corresponding to the first image" may correspond to the first image directly or indirectly to the first image. An indirect correspondence refers to, for example, a situation corresponding to the first image information. The first image information is information about the first image, such as the first image itself, or the attributes of the first image, and the like.

The second image information candidate set storage unit 33 is preferably a non-volatile storage medium, but may be implemented by a volatile storage medium. The process of storing the second image information candidate set in the second image information candidate set storage unit 33 is not a problem.

The candidate output unit 34 outputs one or more second image information candidate sets stored in the second image information candidate set storage unit 33. When the instruction accepting unit 103 receives the instruction to output the second image information candidate set, the candidate output unit 34 may output one or more second image information candidate sets stored in the second image information candidate set storage unit 33. The so-called output here is usually the display to the display, the projection of the projector, and the concept of transmitting signals to an external device or other program.

The second image storage unit 35 is one or more second images corresponding to candidates for one or more pieces of second image information corresponding to the instruction accepted by the instruction accepting unit 103, and corresponding to the second image. The first image of the information candidate set is stored in the second image storage unit 32 correspondingly. For example, when the second image information is the second image, the second image storage unit 35 associates one or more second images corresponding to the instruction received by the instruction accepting unit 103 with the first image. It is stored in the second image storage unit 32. Furthermore, for example, when the second image information is an attribute of the image, the second image storage unit 35 constructs the second image using the attributes of the image, and corresponds to the first image. It is stored in the second image storage unit 32. The second image storage unit 35 is usually implemented by an MPU, a memory, or the like. The processing program of the second image storage unit 35 is usually implemented by software, and the soft system is stored in a storage medium such as a ROMM. But it can also be implemented with hardware (dedicated circuit).

The first image related information acquisition unit 36 acquires one or more first image related information from one or more first images of the first image storage unit 31. The first image related information is information about all or a part of the first image. The first image related information is, for example, one or more feature quantities extracted from all or a part of the first image. Further, one or more feature amounts have a near feature quantity that is one of the one or more first image partial feature amounts, and an overall feature quantity that is a feature quantity of one or more first images as a whole. Examples of the near feature quantity and the overall feature quantity have been set forth above, and the description thereof is omitted. Furthermore, the first image related information may be information that degenerates one or more of the above feature quantities. This retracted information is also a feature quantity.

The first image related information acquisition unit 36 is usually implemented by an MPU, a memory, or the like. The processing program of the first image related information acquisition unit 36 is usually implemented by software, and the soft system is stored in a storage medium such as a ROM. But it can also be implemented with hardware (dedicated circuit).

The second image related information acquisition unit 37 acquires one or more second image related information from one or more second images of the second image storage unit 32. The second image related information is information about all or a part of the second image. The second image related information is information used to generate all or a portion of the second image. For example, a parameter group to be used to generate a formula for all or a portion of the second image, or a calculation formula required to generate all or part of the second image. The second image related information may also be, for example, all or part of the second image itself. When the second image related information is, for example, all or part of the second image itself, the second image related information acquiring unit 37 performs a process of dividing the second image into spatiotemporal blocks.

The second image related information acquisition unit 37 is usually realized by an MPU, a memory, or the like. The processing program of the second image related information acquisition unit 37 is usually implemented by software, and the soft system is stored in a storage medium such as a ROM. But it can also be implemented with hardware (dedicated circuit).

The lookup table configuration unit 38 constitutes a lookup table having one or two or more pieces of corresponding information. As described above, the correspondence information is information for causing all or part of one or more first images to correspond to all or a part of one or more second images. Furthermore, the correspondence information is, for example, information that has a correspondence relationship between the first image related information and the second image related information. And corresponding The information is, for example, information having first image related information and second image related information. In addition, the content or structure of the corresponding information is not asked. Meanwhile, the second image related information corresponding to the first image related information, all or a part of the first image as the source of the first image related information, and the second image related information All or part of the second image of the source, the spatial position corresponding to the frame image constituting the image, the temporal position corresponding to the image, the spatial and temporal position of the image Corresponding situation.

The lookup table configuration unit 38 is usually implemented by an MPU, a memory, or the like. The processing program of the second image related information acquisition unit 37 is usually implemented by software, and the soft system is stored in a storage medium such as a ROM. But it can also be implemented with hardware (dedicated circuit).

The lookup table storage unit 39 stores the lookup table included in the lookup table configuration unit 38 in the storage unit 101. In addition, the so-called accumulation here includes a case of writing a memory or the like.

The lookup table storage unit 39 is usually implemented by an MPU or a memory or the like. The processing program of the second image related information acquisition unit 37 is usually implemented by software, and the soft system is stored in a storage medium such as a ROM. However, it can also be implemented by hardware (dedicated circuit).

Next, an operation of the user in selecting the second image suitable for itself in the lookup table acquisition device 3 will be described using the flowchart of FIG.

(Step S1201) The instruction accepting unit 103 determines whether or not the instruction to output the second image information candidate set is accepted. If the instruction is accepted, the process proceeds to step S1202. If the instruction is not accepted, the process returns to step S1201.

(Step S1202) The candidate output unit 34 substitutes 1 for the counter i.

(Step S1203) The candidate output unit 34 determines whether or not the i-th second image information candidate set exists in the second image information candidate set storage unit 33. If there is an i-th second image information candidate set, the process goes to step S1204, and if the i-th second image information candidate set does not exist, the process ends.

(Step S1204) The candidate output unit 34 reads and outputs the i-th second image information candidate set from the second image information candidate set storage unit 33.

(Step S1205) The instruction accepting unit 103 determines whether or not one or two or more second images are accepted from the candidates of the two or more second image information included in the second image information candidate set. Information selection instructions. If the selection instruction has been accepted, the process proceeds to step S1206. If the selection instruction has not been accepted, the process returns to step S1205.

(Step S1206) The second image storage unit 35 acquires one or more candidates for the second image information corresponding to the instruction accepted in step S1205.

(Step S1207) The second image storage unit 35 acquires the second image using the second image information acquired in step S1206, and accumulates in the second image storage unit 32 in association with the first image. The first image is a first image corresponding to the i-th second image information candidate set.

(Step S1208) The candidate output unit 34 increments the counter i by one. Going back to step S1203.

Next, an operation of the lookup table acquisition means 3 to construct a lookup table and store it will be described using the flowchart of FIG. Further, the second image corresponding to each of the first images stored in the first image storage unit 31 is stored in the second image storage unit 32.

(Step S1301) The first image related information acquisition unit 36 substitutes 1 for the counter i.

(Step S1302) The first image related information acquisition unit 36 determines whether or not the i-th first image is stored in the first image storage unit 31. If the i-th first image is stored, the process proceeds to step S1303, and if not, the process ends.

(Step S1303) The first image related information acquisition unit 36 reads the i-th first image from the first image storage unit 31.

(Step S1304) The first image related information acquisition unit 36 divides the i-th first image read in step S1303 into blocks. Next, the first image related information acquisition unit 36 acquires n first spatiotemporal blocks.

(Step S1305) The second image related information acquisition unit 37 reads the i-th second image from the second image storage unit 32.

(Step S1306) The second image related information acquisition unit 37 divides the i-th second image read in step S1305 into blocks. Next, the second image related information acquisition unit 37 acquires n second spatiotemporal blocks.

(Step S1307) The lookup table constructing unit 38 substitutes 1 into the counter j.

(Step S1308) The lookup table constructing unit 38 judges whether or not the jth block exists in the spatiotemporal block obtained in step S1304. If the jth block exists, the process goes to step S1309, and if the jth block does not exist, it goes to step S1314.

(Step S1309) The first image related information acquisition unit 36 acquires the first image related information from the jth block of the i-th first image.

(Step S1310) The second image related information acquisition unit 37 acquires the second image related information from the jth block of the i-th second image.

(Step S1311) The lookup table configuration unit 38 constitutes correspondence information including the first image related information acquired in step S1309 and the second image related information obtained in step S1310.

(Step S1312) The lookup table storage unit 39 accumulates the correspondence information constituted by the step S1311 in the storage unit 101.

(Step S1313) The lookup table constructing unit 38 increments the counter j by one. The process returns to step S1308.

(Step S1314) The first image related information acquisition unit 36 increments the counter i by one. The process returns to step S1302.

The specific operation of the lookup table acquisition device 3 of the present embodiment will be described below.

First, an operation example in which the lookup table acquisition device 3 accepts an instruction to select a second image from the user and accumulates the second image will be described.

Now, a plurality of second image information candidate sets as shown in FIG. 14 are stored in the second image information candidate set storage unit 33. Further, here, it is assumed that the image of the candidate 1 is the first image in the second image information candidate set. Further, among the second image information candidate sets, the candidates 1 to 4 are candidates for the second image. That is, here, the second image information is the second image itself.

Next, the user inputs an instruction to output the second image information candidate set to the lookup table acquisition means 3, and the instruction accepting unit 103 accepts an instruction to output the second image information candidate set.

Next, the candidate output unit 34 reads and outputs the first second image information candidate set (the set of the stored images of "ID=1" in Fig. 14). An example of the output of such a second image information candidate set is Fig. 15.

Next, the user enters a selection indication (eg, "4") that matches the image of his or her preference. Next, the instruction accepting unit 103 accepts an instruction (for example, "4").

Then, the second image storage unit 35 acquires the fourth image corresponding to the instruction and stores it in the second image storage unit 32.

For the other second image information candidate sets, the above processing is also performed, so that the second image that the user likes is stored in the second image storage unit 32.

Next, a specific operation of the lookup table acquisition means 3 and storing the lookup table will be described. Here, seven specific examples are used for explanation.

(Specific example 1)

The specific example 1 is an example in which the same subject is photographed with a light source of a different light amount, and the obtained first image and second image are used.

First, the light source of the light amount A is irradiated onto one subject, and is photographed by an imaging device (not shown) to acquire the first image and accumulated in the first image storage unit 31. Further, the light source B (light amount B > light amount A) is irradiated onto the one subject, and is imaged by an imaging device (not shown) to acquire a second image and accumulated in the second image storage unit 32. In this case, the second image is an image in which the brain load is reduced compared to the first image. Moreover, it is preferable to visually feel that the taste of the second image is higher than the first image. The image having a high perceived quality is an image showing the texture, the sense of distance, the sense of air, the warmth, the transparency, the freshness, or the high-grade feeling of the subject.

Further, the subject to be photographed by changing the amount of light of the light source is preferably a natural, human, animal, still life, or the like. Further, depending on the subject, there may be cases where the degree of change in the amount of light of the light source is different, and it is needless to say.

By the above manner, the first image storage unit 31 and the second image storage unit 32 can be created.

Next, the first image related information acquisition unit 36 sequentially reads the first image from the first image storage unit 31. Next, the first image related information acquisition unit 36 divides the first image into blocks, and obtains n first spatiotemporal blocks. In addition, a plurality of first space-time blocks may also have overlapping regions. In other words, the division processing by the first image related information acquisition unit 36 and the division processing performed by the division unit 105 are the same processing.

At the same time, the second image related information acquisition unit 37 also reads the second image corresponding to the first image from the second image storage unit 32. Next, the second image related information acquisition unit 37 divides the second image into blocks to obtain n second spatiotemporal blocks.

Next, the first image related information acquisition unit 36 acquires the maximum value and the minimum value of the plurality of pixels, the dynamic range, the luminance power number distribution, and the time direction difference value from each block of the first image (for example, and just before The difference value of the corresponding pixel of the field) and so on. This information is a feature quantity vector and is the first image related information. The first image related information is obtained for each block.

Next, the second image related information acquisition unit 37 acquires one or more parameters required to generate a block from each block of the second image. Specifically, the second image related information acquisition unit 37 acquires, for example, the feature vector of each block of the second image, and substitutes the feature vector into the calculation formula to acquire one or more parameters. Further, one or more parameters are examples of the second image related information.

Next, the lookup table constructing unit 38 constructs corresponding information having the first image related information and the second image related information for each of the blocks. Then, the corresponding correspondence information is stored in the storage unit 101 by the lookup table storage unit 39.

Through the above processing, a lookup table having a plurality of corresponding information is generated. In addition, the same or similar first image related information may also be summarized into one corresponding information.

(Specific example 2)

The specific example 2 is an example in which the same subject is photographed using a light source of a different color, and the obtained first image and second image are used.

First, a light source that emits an X color (for example, white) to a subject is imaged by an imaging device (not shown) to acquire a first image, and is stored in the first image storage unit 31. Then, a light source that emits a Y color (for example, orange) to the subject is imaged by an imaging device (not shown) to acquire a second image, and is stored in the second image storage unit 32. In this case, from a human point of view, it is necessary to feel that the second image has a higher grade than the first image.

In addition, the subject to be photographed by changing the color of the light source is preferably a natural, human, animal, still life, or the like. Moreover, depending on the subject, the degree of change in the color of the light source may be different, and it is needless to say.

In the above manner, the first image storage unit 31 and the second image storage unit 32 can be created. The processing after the first image storage unit 31 and the second image storage unit 32 are established is the same as that of the specific example 1, and therefore the description thereof will be omitted.

(Specific example 3)

The specific example 3 is an example in which the same subject is photographed by a light source disposed at a different position, and the obtained first image and second image are used.

First, a light source provided at the position α is irradiated onto one subject, and an image is taken by an imaging device (not shown) to acquire a first image and stored in the first image storage unit 31. Further, a light source provided at the position β (a position where a large back surface of the subject is generated compared to the position at the position α) is irradiated onto the one subject, and is imaged by an imaging device (not shown). The second image is acquired and stored in the second image storage unit 32. In this case, as far as the person is concerned, the negative image area of the subject produced by the second image must be larger than the first image, and the stereoscopic effect of the subject can be more felt.

Furthermore, it is preferable to use a natural light, a human, an animal, a still life, and the like to change the position of the light source to be photographed. In addition, depending on the subject, the degree of change in the position of the light source may vary, and it should be understood.

In the above manner, the first image storage unit 31 and the second image storage unit 32 can be created. The processing after the first image storage unit 31 and the second image storage unit 32 are established is the same as that of the specific example 1, and therefore the description thereof will be omitted.

(Specific example 4)

The specific example 4 is an example in which the same subject is photographed with a light source having different light amounts and disposed at different positions, and the obtained first image and second image are used.

First, a light source disposed at the position α and having the light amount A is irradiated onto one subject, and is photographed by an imaging device (not shown) to acquire a first image and stored in the first image storage unit 31. Further, a light source disposed at the position β and having the light amount B (light amount B>light amount A) is irradiated onto the one subject, and is imaged by an imaging device (not shown) to obtain a second image. The image is stored in the second image storage unit 32. In this case, it is more appropriate for a person to feel that the taste of the second image is higher than the first image.

Further, it is preferable that the subject to be photographed by changing the amount of light of the light source is natural, human, animal, still life, and the like.

In the above manner, the first image storage unit 31 and the second image storage unit 32 can be created. The processing after the first image storage unit 31 and the second image storage unit 32 are established is the same as that of the specific example 1, and therefore the description thereof will be omitted.

(Specific example 5)

The specific example 5 is an example in which the same subject is photographed in an environment in which one or more factors of weather, temperature, and humidity are different, and the obtained first image and second image are used.

First, in an environment where the weather is "female", the temperature is "25 degrees", and the humidity is "40%", the light source is irradiated onto one subject, and the image is taken by an imaging device (not shown) to obtain the first image. It is stored in the first image storage unit 31. Further, in an environment where the weather is "female", the temperature is "22 degrees", and the humidity is "70%", the light source is irradiated onto the one subject, and the image is taken by an imaging device (not shown) to obtain a second image. And stored in the second image storage unit 32. In this case, from a visual point of view, the second image is usually more likely to feel a sense of distance, stability, and the like.

In the above manner, the first image storage unit 31 and the second image storage unit 32 can be created. The processing of the first image storage unit 31 and the second image storage unit 32 is the same as that of the specific example 1, and therefore the description thereof will be omitted.

In the same manner, first, the light source is irradiated onto one subject in an environment of "female", "25 degrees", and "40%", and the image is taken by an imaging device (not shown) to obtain the first image. The image is stored in the first image storage unit 31. Further, in an environment where the weather is "clear", the temperature is "28 degrees", and the humidity is "20%", the light source is irradiated onto the one subject, and the image is taken by an imaging device (not shown) to obtain a second image. And stored in the second image storage unit 32. In this case, as far as people are concerned, the second image is usually more sensible to the sense of air - warmth and the like.

In the above manner, the first image storage unit 31 and the second image storage unit 32 can be created. The processing of the first image storage unit 31 and the second image storage unit 32 is the same as that of the specific example 1, and therefore the description thereof will be omitted.

(Specific example 6)

The specific example 6 is an example in which a first image and a second image obtained by an imaging device capable of capturing images of different depths of field are used.

First, a photographing device for photographing a shallower depth image is used, and a light source is irradiated onto one subject to obtain a first image, which is stored in the first image storage unit 31. Further, an imaging device that photographs a deep-depth image is used, and a light source is irradiated onto the one subject, and is captured by an imaging device (not shown) to acquire a second image and stored in the second image storage unit 32. . In this case, as far as people are concerned, since the focus can be more aligned overall, the second image can usually make people feel clear and has improved. Moreover, the sense of levelness of the second image in the depth will increase, and a sense of depth and a sense of three-dimensionality are generally obtained.

In the above manner, the first image storage unit 31 and the second image storage unit 32 can be created. The processing of the first image storage unit 31 and the second image storage unit 32 is the same as that of the specific example 1, and therefore the description thereof will be omitted.

(Specific example 7)

Specific Example 7 is an example of using a first image and a second image obtained by a photographing device having different shutter speeds.

The light source is irradiated onto one subject, and the first image is acquired by the imaging device having a slow shutter speed (shutter speed=A), and is stored in the first image storage unit 31. Further, the light source is irradiated onto the one subject, and an imaging device having a fast shutter speed (shutter speed=B, A<B) is imaged by an imaging device (not shown) to acquire a second image and accumulate The second image storage unit 32. In this case, as far as people are concerned, the second image is usually more sensible to feel the sense of speed or leaps.

In the above manner, the first image storage unit 31 and the second image storage unit 32 can be created. The processing of the first image storage unit 31 and the second image storage unit 32 is the same as that of the specific example 1, and therefore the description thereof will be omitted.

As described above, according to the present embodiment, it is possible to automatically obtain a lookup table that can be used to generate an image in which the brain load is adjusted depending on the purpose.

Further, according to the present embodiment, if the user of the image viewer uses the lookup table acquisition device 3 to create a lookup table, the user can obtain a lookup table that can output an image whose brain load is adjusted according to the purpose.

Further, according to the present embodiment, the processing of selecting the second image by one or more users is performed for each user attribute (before 30 years old, 60 years old or older, female, male, high school student, etc.). Make a lookup table for each user attribute. Moreover, an image processing apparatus (for example, a television receiver) using a lookup table fabricated in this manner can output an image of the adjusted brain load for each user attribute to suit his or her preference.

Further, in the lookup table acquisition device 3 of the present embodiment, some components such as the second image information candidate set storage unit 33, the instruction accepting unit 103, the candidate output unit 34, and the second image storage unit 35 may not be provided. There should be no rumors.

Further, the lookup table obtained by the lookup table acquisition device 3 of the present embodiment is suitable for copying and using the image processing devices described in the first and second embodiments.

Further, the soft system for realizing the lookup table acquisition device of the present embodiment is a program as described below. That is, the program is one or more first images stored in the storage medium and one or more second images corresponding to the one or more first images, and each of the second images Compared with the first image, the image is an image with adjusted brain load, and is an image related to the same object as the first or more first images, so that the computer is used as the first image related information. The acquisition unit acquires one or more first image related information from all or part of the one or more first images, wherein the first image related information is related to one or more first images stored in the storage medium All or part of the information; the second image related information acquisition unit acquires one or more second image related information from all or part of the one or more second images, and the second image related information is related to storage Information of all or part of one or more second images of the storage medium; the lookup table forming unit displays all or part of the one or more first images and all of the one or more second images Or a corresponding corresponding information structure One or more lookup tables, and the corresponding information has: first image related information obtained by the first image related information obtaining unit, and corresponding to the first image related information, and the second Image phase The second image related information obtained by the information acquisition unit; and the lookup table storage unit, which stores a lookup table formed by the lookup table configuration unit in a storage medium and functions as a program.

Furthermore, the program preferably stores one or more second image information candidate sets stored in the storage medium, wherein the second image information candidate set corresponds to one or more first images, and is related to a set of candidates of two or more second images that are identical to the one or more first images, and a computer as a candidate output unit that outputs the one or more second image information candidate sets; and an instruction receiving unit; And an instruction to select one or more candidates for the second image in the candidate of the two or more second images included in the one or more second image information candidate sets output by the candidate output unit; and The second image storage unit forms a correspondence between one or more second image candidates corresponding to the instruction received by the instruction accepting unit and the first image corresponding to the second image information candidate set, and A program that functions in the second image storage unit and functions.

(Embodiment 4)

In the present embodiment, a specific example of the process of generating the lookup table by using the lookup table acquisition means 3 will be described.

This specific example is a case where the correspondence information constituting the lookup table is a feature quantity vector and an image conversion filter. Further, the feature amount vector is information extracted from an input image (first image). Furthermore, the image conversion filter is, for example, a set of one or more filter coefficients.

Now, the first image storage unit 31 stores, for example, a plurality of images including the first image having a shallow depth of field shown in FIG. Further, in the second image storage unit 32, for example, a plurality of images including the second image having a deep depth of field shown in FIG. 17 are stored. In addition, some of the first images and some of the second images have a corresponding relationship. That is, for example, the first image of FIG. 16 and the second image of FIG. 17 have a corresponding relationship.

Moreover, the depth of field of the second image is deeper than the first image. In addition, the depth of field in Figure 16 is shallow, and the focal length is opposite the red car (dark car) in front of the image. On the other hand, the depth of field in Figure 17 is deep, and the focal length is opposite the yellow car (light car) behind the image. Furthermore, in general, compared with the first image, the second image with a deeper depth of field, the overall image is easier to understand, and can be said to be a better image with less brain load.

In this case, it is assumed that an instruction to establish a lookup table is input from the user. Next, the first image related information acquisition unit 36 reads the first image from the first image storage unit 31 (here, for example, FIG. 16). Then, the first image related information acquisition unit 36 divides the first image and acquires a plurality of spatiotemporal blocks. Here, as shown in FIG. 18, the first image related information acquisition unit 36 divides the first image into 16 and acquires 16 first spatiotemporal blocks. Further, in Fig. 18, each of the first space-time blocks is described with a block identifier.

Next, the second image related information acquisition unit 37 reads the second image from the second image storage unit 32 (here, for example, FIG. 17). Then, the second image related information acquisition unit 37 divides the second image to obtain a plurality of spatiotemporal blocks. Here, as shown in Fig. 19, the second image related information acquisition unit 37 divides the second image into 16 and acquires 16 second spatiotemporal blocks. Further, in Fig. 19, the block identifier is described in each of the second space-time blocks.

Next, the lookup table constructing unit 38 converts the first first spatiotemporal block of the first image into the first second spatiotemporal block of the second image using, for example, a least squares estimate. The filter factor of the conversion filter.

Similarly, the lookup table constructing unit 38 sequentially converts the nth (n is 2 to 16) first spatiotemporal block of the first image into the nth of the second image using, for example, the least squares estimation method ( n is the filter coefficient of the conversion filter of the second space-time block of 2 to 16).

In the above manner, the filter coefficients of the 16 image conversion filters can be obtained. In addition, FIG. 20 is a conceptual diagram for explaining an execution operation of the lookup table configuration unit 38. In Fig. 20, F ₀₄ denotes a fourth image conversion filter, and F ₁₅ denotes a 15th image conversion filter.

Next, the lookup table constructing unit 38 obtains the near feature quantity of each of the 16 first spatiotemporal blocks of the first image. Further, for example, the lookup table constructing unit 38 calculates a frequency component using a discrete fourier transform for each first spatiotemporal block, and obtains a power of each domain. The power of each of the fields is used as the feature quantity vector of the near feature quantity. Moreover, the concept of such processing is disclosed in Figure 21. In Fig. 21, for example, the lookup table constructing unit 38 obtains the feature quantity vector "α ₀₄ = (p _04-1 , p _04-2 , p _{04-3 ) of the} near feature quantity from the fourth first space-time block. p _04-4 )", the feature quantity vector "α ₁₅ =(p _15-1 , p _15-2 , p _15-3 , p _15-4 )" of the near feature feature is obtained from the 15th first space-time block. .

Next, the lookup table configuration unit 38 calculates the overall feature amount of the feature amount of the entire first image. For example, the lookup table constructing unit 38 calculates the dispersion "A ₁ = (V ₁ , V ₂ , V ₃ , V ₄ )" of each component of the locally obtained feature quantity vector (the vector of the near feature quantity) as an overall feature. the amount. Moreover, this processing concept is disclosed in Figure 22.

Next, the lookup table constructing unit 38 connects the overall feature quantity and the near feature quantity of each of the areas to form a feature quantity vector "(A ₁ , α ₀₁ ), etc." for constructing the corresponding information. Further, the lookup table constructing unit 38 constitutes correspondence information corresponding to the feature amount vector and the filter coefficient.

Next, the lookup table storage unit 39 accumulates 16 pieces of correspondence information corresponding to the feature amount vector and the filter coefficient in the storage unit 101.

The above processing is performed on the first image and the second image of the other groups. Then, the lookup table obtaining means 3 obtains the lookup table shown in Fig. 23. The lookup table of Figure 23 has a plurality of corresponding information. Further, here, the corresponding information has a feature amount vector and a filter coefficient.

As described above, in the present embodiment, it is possible to automatically obtain a lookup table that can be used to generate an image for adjusting the brain load depending on the purpose.

(Embodiment 5)

In the present embodiment, an image processing apparatus 4 that obtains an image of a brain load adjustment on an image to be accepted according to the purpose using the lookup table created in the fourth embodiment will be described.

Fig. 24 is a block diagram showing the image processing apparatus 4 of the embodiment. The image processing device 4 includes a storage unit 101, an image receiving unit 104, a dividing unit 105, an image analyzing unit 106, a mapping unit 107, a synthesizing unit 108, and an image output unit 109.

Now, the storage unit 101 of the image processing apparatus 4 stores the lookup table shown in Fig. 23. In addition, the lookup table is preferably indexed with a feature quantity vector as a key. Moreover, the lookup table preferably classifies the corresponding information with the feature quantity vector as a key.

At the same time, it is assumed that the image receiving unit 104 has accepted the image shown in FIG. In addition, the image of Fig. 25 is an image with a shallow depth of field.

Next, the image analysis unit 106 calculates the overall feature amount (A _n ) of the image of Fig. 25. Further, the calculation method of the overall feature amount is the same processing as that described in the fourth embodiment.

Next, the image analysis unit 106 calculates the near feature quantity (α _n ) for each pixel of the image of Fig. 25 . Here, the Kinki feature quantity is used to calculate the frequency components in the near 16×16 pixel block of the pixel to obtain the power of each field. Further, this processing is the same as the processing described in the fourth embodiment.

Then, the image analysis unit 106 forms a feature amount vector (A _n , α _n ) obtained by combining the total feature quantity and the near feature quantity for each pixel.

Next, the image analysis unit 106 calculates the distance between the feature quantity vector (A _n , α _n ) corresponding to each pixel and the two or more feature quantity vectors of the two or more pieces of corresponding information constituting the lookup table, and determines the closest distance. The feature quantity vector "for example, (A _m , α _m )".

Then, the mapping unit 107 acquires a filter coefficient "for example, F _m " that is paired with the closest feature quantity vector for each pixel.

Next, the mapping unit 107 applies a conversion filter realized by the obtained filter coefficients to each pixel of the input image to acquire each pixel of the second image (output image).

Next, the synthesizing unit 108 forms an output image by using the acquired pixels as the output pixel values of the pixel positions of the input image. Then, the image output unit 109 outputs the constructed output image. The concept of the above processing is disclosed in Figure 26.

As described above, according to the present embodiment, an image in which the brain load is appropriately adjusted can be output.

Further, in the present embodiment, the method of acquiring the feature quantity vector constituting the lookup table and the method of acquiring the feature quantity vector of the image analysis unit 106 are not the same. The method of acquiring the feature quantity vector constituting the lookup table and the method of acquiring the feature quantity vector of the image analysis unit 106 may be the same.

(Embodiment 6)

In the present embodiment, an image processing apparatus 5 that acquires an image whose brain load has been adjusted in accordance with the accepted image using a lookup table will be described. Further, in the present embodiment, the main difference from the first embodiment and the like is that the applied restriction conditions are dynamically changed in accordance with the input image.

Fig. 27 is a block diagram showing the image processing apparatus 5 of the embodiment.

The image processing device 5 includes a storage unit 101, a restriction condition storage unit 502, an instruction reception unit 503, an image reception unit 104, a division unit 105, an image analysis unit 106, a mapping unit 507, a synthesis unit 108, and an image output unit. 109. The restriction condition changing unit 510.

The mapping unit 507 includes, for example, an output image candidate acquiring device 1072, a determining device 1073, a feature amount acquiring device 5071, a restriction condition determining device 5072, a changing device 5074, and an output image obtaining device 1075.

The restriction condition storage unit 502 can store two sets of restriction information on the above-mentioned pair of storage condition identification information and restriction conditions. The limitation here is described by taking the condition of the output image as an example, but it may also be a condition regarding the input image or the corresponding information. Conditional identification information is information used to identify restrictions. The condition identification information is, for example, a feature amount vector. Further, the feature quantity of the constituent vector is, for example, the near-field spatial activity value of the input image. The near-temporal spatial activity value may have, for example, a time difference value of a pixel at the same position on the field, a tilt (primary and secondary spatial differential value), a minimum value and a maximum value (a 1-bit value), an n-bit value, a dynamic range, Various values such as spatial difference values, pixel value dispersion, power of high frequency regions in space, ratio of time activity value to spatial activity value. Also, the restriction is an appropriate near-field activity value. In addition, examples of restraint information are disclosed in Figure 28. In Fig. 28, the constraint information has: a near-spatial activity value which is a conditional identification information, and an appropriate activity value which is a restriction condition.

The instruction accepting unit 503 accepts an instruction to change the restriction condition from the user. Further, the indication is, for example, an instruction to correct the restriction information of Fig. 28. Further, the instruction is, for example, an instruction to change the amount of stimulation received by the user from the image.

The feature amount acquisition device 5071 that constitutes the map unit 507 acquires the feature amount vector of the image (input image) accepted by the image accepting unit 104. The feature amount acquiring means 5071 can also acquire the feature amount vector of all the images accepted by the image accepting unit 104, and can acquire the feature amount vector of the spatiotemporal block constituting the image accepted by the image accepting unit 104.

The restriction condition determining means 5072 applies the feature amount vector acquired by the feature amount acquisition means 5071 to the restriction information of the restriction condition storage unit 502 to select a restriction condition. More specifically, the restriction condition determining means 5072 selects the condition identification information closest to the feature amount vector acquired by the feature amount obtaining means 5071 (the condition identification information is also the feature quantity vector) The restriction condition storage unit 502 acquires a restriction condition paired with the selected condition identification information.

When the judging means 1073 determines that the restriction condition is not satisfied, the changing means 5074 changes all or a part of the second image using the restriction condition acquired by the restriction condition determining means 5072. Further, when the judging means 1073 determines that the restriction condition is not satisfied, the changing means 5074 may change the lookup table. Further, when the judging means 1073 determines that the restriction condition is not satisfied, the changing means 5074 may change the input image accepted after the judgment, or the space-time block obtained after the judgment, or one of the input images accepted after the judgment. The above feature amount or one or more feature amounts of the space-time block obtained after the determination is changed.

The restriction condition changing unit 510 changes the restriction information based on the instruction accepted by the instruction accepting unit 503. Furthermore, the restriction condition changing unit 510 can also automatically change the restriction information. In other words, the restriction condition changing unit 510 may be based on, for example, user attributes (age, gender, address, etc.), information superimposed on the broadcast (information included in the EPG, etc.), time, time zone, external sensor Information (such as the brightness of the room, temperature, etc.), automatically change the binding information. In this case, the restriction condition changing unit 510 stores in advance information on how the restriction information is to be changed in accordance with the user attribute or the like (for example, a correspondence table in which the user attribute and the formula of the change calculation method are displayed). Moreover, when an external sensor is used, the restriction condition changing unit 510 acquires information (brightness, temperature, and the like of the room) from a sensor (not shown).

The restriction condition storage unit 502 is preferably a non-volatile storage medium, but may be realized by a volatile storage medium. The process of storing the restraint information in the restriction condition storage unit 502 is not a question. For example, the restriction information stored in the storage medium may be stored in the restriction storage unit 502, and the restriction information transmitted via the communication line or the like may be stored in the restriction storage unit 502, or the restriction information input via the input device may be stored in the restriction. Condition storage unit 502.

The instruction accepting unit 503 can be realized by a device driver of an input device such as a keyboard or a control software for a menu screen.

The mapping unit 507, the restriction condition changing unit 510, the feature amount acquiring device 5071, the restriction condition determining device 5072, and the changing device 5074 are usually realized by an MPU, a memory, or the like. The processing program of the mapping unit 507 or the like is usually implemented by software, and the soft system is stored in a storage medium such as a ROM. However, it can also be implemented by hardware (dedicated circuit).

Next, the operation of the image processing apparatus 5 will be described using the flowchart of FIG. In the flowchart of Fig. 29, steps different from the flowchart of Fig. 2 will be described.

(Step S2901) The mapping unit 507 performs mapping processing. The mapping process is explained using the flowchart of FIG.

(Step S2902) The instruction accepting unit 503 determines whether or not the user's instruction is accepted. If the user's instruction is accepted, the process proceeds to step S2903. If the user's instruction is not accepted, the process returns to step S201.

(Step S2903) The restriction condition changing unit 510 changes the restriction information based on the instruction received by the instruction accepting unit 503.

Further, in the flowchart of Fig. 29, the input image is divided and processed for each spatiotemporal block. However, in the flowchart of Fig. 29, the entire input image can also be processed.

Next, the mapping process related to step S2901 will be described using the flowchart of FIG. In the flowchart of Fig. 30, steps different from the flowchart of Fig. 4 will be described.

(Step S3001) The feature amount acquiring means 5071 constituting the mapping unit 507 acquires the feature amount vector of the image accepted by the image accepting unit 104.

(Step S3002) The restriction condition determining means 5072 applies the feature amount vector acquired by the feature amount acquisition means 5071 to the restriction information of the restriction condition storage unit 502 to determine the restriction condition. This restriction condition determination processing will be described using the flowchart of Fig. 31.

Next, the restriction condition determination processing in step S3002 will be described using the flowchart of FIG.

(Step S3101) The restriction condition determining means 5072 substitutes 1 for the counter i.

(Step S3102) The restriction condition determining means 5072 determines whether or not the i-th constraint information exists in the restriction condition storage unit 502. If there is an i-th constraint information, the process proceeds to step S3103, and if not, the process proceeds to step S3106.

(Step S3103) The restriction condition determining means 5072 acquires the condition identification information of the i-th constraint information from the restriction condition storage unit 502.

(Step S3104) The restriction condition determining means 5072 calculates the distance between the feature amount vector acquired in step S3001 and the i-th condition identification information. Then, the restriction condition determining means 5072 temporarily stores the distance in the buffer corresponding to the i-th condition identification information.

(Step S3105) The restriction condition determining means 5072 increments the counter i by 1, and returns to step S3102.

(Step S3106) The restriction condition determining means 5072 acquires, from the restriction condition storage unit 502, a restriction condition in which the condition identification information having the smallest distance from the feature amount vector acquired in step S3001 is paired. Return to the upper processing.

As described above, according to the present embodiment, an output image conforming to the restriction condition can be configured by changing the restriction conditions used for the input image, and an extremely high quality image can be output.

Further, in the present embodiment, the restriction condition determining means 5072 changes and acquires the restriction condition used in accordance with the input image. However, the restriction condition determining means 5072 may also change the restriction conditions used in accordance with the output image. Further, the restriction condition determining means 5072 can also change the restriction conditions used depending on the input image and the output image.

Furthermore, in the present embodiment, the division unit 105 divides the image accepted by the image reception unit 104. However, the image accepted by the image receiving unit 104 may not be divided. In this case, the division unit 105 is not required in the image processing apparatus 5. In this case, the same applies to other embodiments.

(Embodiment 7)

In the present embodiment, an image processing device 6 that acquires an image of a brain load depending on the purpose of the received image using a lookup table will be described. Further, in the present embodiment, the main difference from the first embodiment and the like is that the applied lookup table is dynamically changed in accordance with the input image or the output image.

Figure 32 is a block diagram of the image processing device 6 of the present embodiment.

The image processing device 6 includes a storage unit 101, a restriction condition storage unit 502, an instruction reception unit 603, an image reception unit 104, a division unit 105, an image analysis unit 106, a mapping unit 607, a synthesis unit 108, and an image output unit. 109. The LUT change information changing unit 610.

Further, the mapping unit 607 includes, for example, an output image candidate acquisition device 1072, a determination device 1073, a first feature amount acquisition device 6071, a second feature amount acquisition device 6072, an LUT change information storage device 6073, an LUT determination device 6074, and a change device. 5074 and an output image acquisition device 1075.

Here, the storage unit 101 stores two or more lookup tables (hereinafter referred to as "LUT (Look Up Table)".

The instruction accepting unit 603 receives an instruction necessary to change the LUT change information to be described later from the user. The indication is, for example, an indication that the amount of stimulation received by the user from the image is changed.

The first feature amount acquisition means 6071 constituting the mapping unit 607 acquires the feature amount vector of the image accepted by the image accepting unit 104. The first feature amount acquisition means 6071 performs the same operation as the above-described feature amount acquisition means 5071. Further, the feature amount vector acquired by the first feature amount acquisition means 6071 is referred to as a first feature amount vector.

The second feature amount acquisition means 6072 acquires the feature amount vector of the output image obtained by the output image acquisition means 1075. The source of the acquired second feature amount obtaining means 6072 is different from the first feature amount obtaining means 6071, but the operation performed is the same as that of the first feature amount obtaining means 6071. Further, one or more feature amounts acquired by the first feature amount acquisition device 6071 and one or more feature amounts acquired by the second feature amount acquisition device 6072 may all be the same feature amount, or may partially include the same feature. The quantity can also be a different feature quantity for all. Further, the feature amount vector acquired by the second feature amount acquisition means 6072 is referred to as a second feature amount vector.

The LUT change information storage means 6073 stores LUT change information for changing the information of the LUT to be used when the image candidate output by the output image candidate acquisition means 1072 is acquired. The LUT change information is, for example, a pair of first feature amount vectors and a class identifier for identifying a lookup table. Further, the LUT change information may be, for example, a pair of the second feature amount vector and the category identifier. Moreover, the LUT change information may be, for example, a pair of the first feature amount vector and the second feature amount vector and the category identifier. Further, the LUT change information is, for example, a first feature amount vector, a pair of two or more types of identifiers, and a pair of two or more ratios corresponding to the various class identifiers. Meanwhile, the LUT change information may be, for example, a second feature amount vector, a pair of two or more types of identifiers, and a pair of two or more ratios corresponding to the various class identifiers. Moreover, the LUT change information may be, for example, a first feature quantity vector, a second feature quantity vector, and two The upper type identifier and the pair of two or more ratios corresponding to the various class identifiers. Further, the LUT change information storage device 6073 usually stores two or more LUT change information. Further, the above-described ratio is a ratio corresponding to each LUT when two or more LUTs are mixed to form a new LUT.

Further, an example of the LUT change information management table stored in the LUT change information storage means 6073 is disclosed in FIG. In Fig. 33, the LUT change information management table has a plurality of LUT change information. The LUT change information has "ID", "first feature quantity vector", "second feature quantity vector", "LUT", "ratio". "LUT" is the type identifier. The "ratio" is information showing the mixture ratio of each LUT when forming a new LUT. In addition, the "ratio" is not limited to the ratio, as long as it is any information required to form a new LUT using a plurality of LUTs. The information for constituting the new LUT is, for example, a calculation formula in which elements constituting a plurality of LUTs are used as parameters. The elements constituting the LUT are, for example, elements of a filter or elements of a feature quantity vector.

The LUT determining means 6074 determines the LUT to be used by the output image candidate obtaining means 1072 by using the LUT change information of the LUT change information storage unit 6073. More specifically, the LUT determining means 6074 uses the first feature amount vector, or the second feature amount vector, or the first feature amount vector and the second feature amount vector for the LUT change information to determine the output image candidate obtaining means 1072 The LUT to be utilized. Further, the LUT decision means 6074 may also use the first feature amount vector, or the second feature amount vector, or the first feature amount vector and the second feature amount vector for the LUT change information to constitute the LUT.

Hereinafter, the operation of the LUT determining means 6074 when the LUT change information management table of Fig. 33 is stored in the LUT change information storage means 6073 will be described. The LUT determining means 6074 calculates the distance between the first feature amount vector obtained by the first feature amount obtaining means 6071 and the first feature amount vector of each record in the LUT change information management table. Next, the LUT determining means 6074 calculates the distance between the second feature amount vector obtained by the second feature amount obtaining means 6072 and the second feature amount vector of each record in the LUT change information management table. Then, the LUT decision means 6074 changes each of the records of the information management table by the LUT to obtain, for example, the sum of the two distances. Next, the LUT decision means 6074 determines the record in which the sum of the two distances is the smallest. Next, the LUT determining means 6074 acquires the attribute value of the "LUT" included in the determined record, or the attribute value of the "LUT" attribute value and the "ratio" attribute value of the determined record. When the attribute value of the "LUT" of the determined record has a category identifier, the LUT decision means 6074 will use the The LUT identified by the type identifier determines the LUT to be used as the output image candidate acquisition means 1072. On the other hand, when the attribute value of the "LUT" of the determined record is two or more types of identifiers, the LUT determining means 6074 acquires two or more kinds of class identifiers and attribute values of "ratio" (hereinafter also The matching group simply referred to as the ratio, and the LUTs identified by the two or more kinds of class identifiers are mixed to form a new LUT in a manner consistent with the ratio.

The LUT change information changing unit 610 changes the LUT change information based on the instruction received by the instruction accepting unit 603. At the same time, the LUT change information changing unit 610 can also automatically change the LUT change information. That is, the LUT change information changing unit 610 may, for example, user attributes (age, gender, residence, etc.), information superimposed on the broadcast (information included in the EPG, etc.), time, time zone, external sensor information (eg, audiovisual) The brightness of the room, temperature, etc., automatically change the LUT change information. Further, in this case, the LUT change information changing unit 610 stores in advance information on how to change the LUT change information in accordance with the user attribute or the like. Moreover, when the external sensor information is used, the restriction condition changing unit 510 acquires information (brightness, temperature, and the like of the room) from a sensor (not shown).

The instruction accepting unit 603 can be realized by a device driver of an input device such as a keyboard or a control software for a menu screen.

The mapping unit 607, the LUT change information changing unit 610, the first feature amount obtaining means 6071, the second feature amount obtaining means 6072, and the LUT determining means 6074 are usually realized by an MPU, a memory, or the like. The processing program such as the mapping unit 607 is usually implemented by software, and the software is stored in a storage medium such as a ROM. However, it can also be implemented by hardware (dedicated circuit).

The LUT change information storage device 6073 is preferably a non-volatile storage medium, but can also be implemented with a volatile storage medium. The process of storing the LUT change information in the LUT change information storage device 6073 is not a question. For example, the LUT change information may be stored in the LUT change information storage device 6073 by the storage medium, or the LUT change information transmitted via the communication line or the like may be stored in the LUT change information storage device 6073, or may be input via the input device. The LUT change information is stored in the LUT change information storage means 6073.

Next, the operation of the image processing apparatus 6 will be described using the flowchart of FIG. In the flowchart of Fig. 34, steps different from the flowchart of Fig. 2 will be described.

(Step S3401) The mapping process is performed by the mapping unit 607. The mapping process is explained using the flowchart of Fig. 35.

(Step S3402) The instruction accepting unit 603 determines whether or not the user's instruction is accepted. If the user's instruction is accepted, the process proceeds to step S3403. If the user's instruction is not accepted, the process returns to step S201.

(Step S3403) The LUT change information changing unit 610 changes the LUT change information based on the instruction received by the instruction accepting unit 503.

Next, the mapping process related to step S3401 will be described using the flowchart of FIG. In the flowchart of Fig. 35, steps different from the flowchart of Fig. 4 will be described.

(Step S3501) The first feature amount acquisition means 6071 of the mapping unit 607 acquires the first feature amount vector from the input image accepted by the image accepting unit 104.

(Step S3502) The second feature amount acquisition means 6072 acquires the second feature amount vector from the output image obtained by the output image acquisition means 1075. Further, the output image obtained as the source of the second feature amount vector here is usually the output image just output.

(Step S3503) The LUT determining means 6074 determines the LUT using the first feature amount vector obtained in step S3501 and the second feature amount vector obtained in step S3502. The LUT decision processing for this processing is explained using the flowchart of Fig. 36.

Next, the LUT decision processing relating to step S3503 will be described using the flowchart of Fig. 36.

(Step S3601) The LUT decision means 6074 substitutes 1 for the counter i.

(Step S3602) The LUT determining means 6074 determines whether or not the i-th LUT change information exists. If the i-th LUT change information exists, the process proceeds to step S3603, and if not, the process proceeds to step S3607.

(Step S3603) The LUT determining means 6074 acquires the first feature amount vector of the i-th LUT change information. Next, the LUT decision means 6074 calculates the distance (d1) between the acquired first feature amount vector and the first feature amount vector obtained in step S3501.

(Step S3604) The LUT determining means 6074 acquires the second feature amount vector of the i-th LUT change information. Next, the LUT decision means 6074 calculates the distance (d2) between the acquired second feature amount vector and the second feature amount vector obtained in step S3502.

(Step S3605) The LUT decision means 6074 substitutes the distance (d1) calculated in the step S3603 and the distance (d2) calculated in the step S3604 into the calculation formula, and executes the calculation formula. Then, the LUT decision means 6074 obtains the cost (C) of the i-th LUT change information. Thereafter, the LUT decision means 6074 associates the cost (C) with the i-th LUT change information, and at least temporarily accumulates it. In addition, the calculation formula is a calculation formula using two distances as parameters, and each distance is used as a function of the parameter. In addition, this function is usually a function of adding each distance as a parameter. The calculation formula is, for example, "C = a1 × d1 + (1 - a1) × d2". Further, a1 is, for example, 0.5, 0.8, or the like.

(Step S3606) The LUT decision means 6074 increments the counter i by one. Going back to step S3602.

(Step S3607) The LUT determining means 6074 acquires one or more types of identifiers included in the LUT change information having the smallest cost calculated in step S3605.

(Step S3608) The LUT determining means 6074 determines whether or not the type identifier acquired in step S3607 is a complex number. If it is a plural, it progresses to step S3609; if it is one, it goes to step S3611.

(Step S3609) The LUT determining means 6074 obtains a plurality of ratios of the LUT change information having the smallest cost from the LUT change information storage means 6073 so as to correspond to the type identifier.

(Step S3610) The LUT determining means 6074 acquires the LUT corresponding to the plurality of type identifiers from the storage unit 101. Then, the LUT decision means 6074 mixes the acquired LUTs according to the ratio obtained in step S3609, and generates a new LUT. This new LUT is the LUT to be used by the output image candidate acquisition means 1072.

Further, the mixing of the LUT is, for example, the following processing. For example, the corresponding information constituting the LUT is a feature quantity vector and a parameter group (for example, a set of coefficients of a filter). Moreover, a plurality of LUTs have the same feature quantity vector. At the same time, the LUT decision means 6074 obtains a parameter group of a plurality of LUTs corresponding to the same feature quantity vector, and mixes the parameters constituting the parameter group by the ratio. For example, a corresponding information of the LUT "A" has a feature quantity vector of V1 and a parameter group of (4, 10, 7, ‧ ‧) Moreover, the feature quantity of a corresponding information of the LUT "B" The vector is V1 and the parameter group is (10,8,17,‧‧‧). Then, the ratio corresponding to the LUT "A" is "a1", and the ratio corresponding to the LUT "A" is "1-a1". In this case, the LUT decision means 6074 obtains the parameter group (4 × a1 + 10 × (1 - a1), 10 × a1 + 8 × (1 - a1), 7 × a1 + 17 × (1 - a1), ‧ ‧‧). This is done for all corresponding information.

(Step S3611) The LUT determining means 6074 acquires the LUT identified by the type identifier of the LUT change information having the lowest cost from the LUT change information storage means 6073. Such an LUT is an LUT used by the output image candidate acquisition device 1072.

As described above, according to the present embodiment, by changing the applied lookup table and the output image in accordance with the input image, the output image, or the input image and the output image, the output quality can be extremely high. image.

(Embodiment 8)

In the present embodiment, the image learning device 7 will be described. The image learning device 7 is a device for the lookup table acquisition device 3 to acquire the first image and the second image used for the lookup table. Furthermore, the image learning device 7 herein is mainly used to enhance the look-up table of the entertainment image processing device.

Figure 37 is a block diagram of the image learning device 7. The image learning device 7 includes a first image storage unit 31, a second image storage unit 32, an image generation unit 71, and an image storage unit 72. Further, the first image storage unit 31 and the second image storage unit 32 constitute means for the lookup table acquisition device 3 and the like.

The first image storage unit 31 may store one or more first images. The first image storage unit 31 can also be stored as the first image of the animation.

The second image storage unit 32 has to store one or more second images. The second image storage unit 32 can also be stored as a second image of the animation.

The image generation unit 71 generates a second image from the first image stored in the first image storage unit 31. At the same time, the image generating unit 71 can also generate the first image from the second image stored in the second image storage unit 32.

For example, the image generation unit 71 generates the following second image or first image.

(1) Generation of a second image in which a shiny image of a white image is inserted.

The image generating unit 71 reads the first image as an animation from the first image storage unit 31. Next, the image generating unit 71 inserts the frame of the white image into an arbitrary frame position of the first image, and acquires the second image.

(2) The generation of a second image in which a shiny image whose image has been increased in brightness value is inserted.

The image generating unit 71 reads the first image as an animation from the first image storage unit 31. Next, the image generation unit 71 increases the frame luminance value of an arbitrary frame position of the first image, and acquires the second image.

(3) Generation of a second image inserted with a shiny image for a high contrast image

The image generating unit 71 reads the first image as an animation from the first image storage unit 31. Next, the image generating unit 71 inserts the high contrast image into an arbitrary frame position of the first image and acquires the second image.

(4) The image emphasizes the generation of the second image of the uneven picture

The image generating unit 71 reads the first image as an animation from the first image storage unit 31. Next, the image generation unit 71 obtains a second image by applying edge enhancement, contrast change, or the like to the frame at an arbitrary position of the first image. Processing such as edge enhancement or contrast change is a well-known technique, and the description thereof is omitted.

(5) Processing of film like images

The image generating unit 71 reads an animated second image as a film source from the second image storage unit 32. Next, the second image is image-converted and the first image is obtained.

The image storage unit 72 accumulates the second image generated by the image generation unit 71 in the second image storage unit 32. At the same time, the image storage unit 72 stores the first image generated by the image generating unit 71 in the first image storage unit 31.

Next, the mapping processing of the image processing apparatus will be described. The mapping process is performed by the mapping section of the image processing apparatus described above.

When the second image is a blinking image generated by any of the above (1) to (3), the mapping unit 107 uses the feature amount vector of the input image (for example, the luminance distribution or the total screen shift amount, etc.) The vector generated by the element) obtains the corresponding information corresponding to the feature quantity vector from the LUT. then, The mapping unit 107 inserts the special frame using the acquired corresponding information. Further, the feature amount vector of the input image is acquired by the image analysis unit 106. Further, when the feature amount vector of the input image satisfies a predetermined condition (which may also be corresponding information), the mapping unit 107 may insert a special frame. The so-called special frame refers to the frame of the shiny image.

Further, when the second image is the emphasized unevenness image generated by the above (4), the mapping unit 107 can perform the above-described processing to emphasize that the non-full screen is uniform, for example, automatically select different according to the waveform. Emphasis on the method.

Further, when the second image is the film-shaped image generated in the above (5), the mapping unit 107 can output an output image converted into a film-like image by performing the above-described processing.

Further, for example, the first image and the second image obtained by capturing the same subject in different illumination environments may be stored in the first image storage unit 31 and the second image storage unit 32, respectively. As described above, the different lighting environments are, for example, environments in which the brightness of illumination is different depending on the subject. Moreover, the so-called different lighting environments are, for example, environments in which the positions of the light sources are staggered.

In this case, the mapping unit 107 can enhance the texture of the image or obtain an image in which the surface reflection characteristics are completely different by performing the above-described processing. For example, the newly created stringed instrument in the input image is output in the form of a lacquered string instrument.

Further, Fig. 38 shows an appearance of a computer which executes the program described in the present specification to realize the lookup table acquisition device and the like of the above embodiment. The above embodiments are implemented by a computer hardware and a computer program executed therein. 38 is an overview of the computer system 340, and FIG. 39 is a block diagram of the computer system 340.

In Fig. 38, computer system 340 includes an FE driver, a computer 341 including a CD-ROM drive, a keyboard 342, a mouse 343, and a display 344.

In Fig. 39, the computer 341 includes, in addition to the FE driver 3411 and the CD-ROM drive 3412, an MPU 3413, a busbar 3414 connected to the CD-ROM drive 3412 and the FD driver 3411, and a ROM 3415 for storing a program such as a boot program. The command to store the application also provides temporary storage space for the RAM 3416 and a hard drive 3417 for storing applications, system programs and data. Although not shown here, only the computer 341 can further include a network card that provides connection to the LAN.

The program for causing the computer system 340 to execute the functions such as the lookup table acquisition means of the above-described embodiment may be stored in the CD-ROM 3501 or FD3502, inserted into the CD-ROM drive 3412 or the FD drive 3411, and then transferred to the hard disk 3417. The program can also be transferred to the computer 341 via a network (not shown) and stored on the hard disk 3417 instead of the foregoing. The program is loaded into RAM3416 during execution. You can also load programs directly from the CD-ROM 3501, FD3502 or the Internet.

The program does not necessarily include an operating system (OS) or a third party program that causes the computer 341 to execute functions such as the lookup table acquisition device of the above-described embodiment. The program may also include only the portion of the command that sings out the appropriate function (module) in a controlled state to obtain the desired result. It is well known in what manner the computer system 340 operates, and detailed description thereof is omitted.

In addition, the computer that executes the above program may be singular or plural. In other words, centralized processing can be performed, or distributed processing can also be performed.

Further, in each of the above embodiments, each process (each function) may be implemented by performing centralized processing via a single device (system), or may be implemented by performing distributed processing via a plurality of devices.

The present invention is not limited to the above embodiments, and various modifications can be made without departing from the scope of the invention.

[Industrial availability]

As described above, the image processing apparatus of the present invention has an effect of outputting an image with an adjusted brain load, and is practical as a television receiver or the like.

1‧‧‧Image processing device

101‧‧‧ Storage Department

102‧‧‧Restricted Condition Storage Department

103‧‧‧Directed Reception Department

104‧‧‧Image Reception Department

105‧‧‧ Division

106‧‧‧Image Analysis Department

107‧‧‧ Mapping Department

108‧‧‧Combination Department

109‧‧‧Image Output Department

110‧‧‧ Lookup Table Update Department

1071‧‧‧Type identifier acquisition device

1072‧‧‧ Output image candidate acquisition device

1073‧‧‧Judgement device

1074‧‧‧Change device

1075‧‧‧ Output image acquisition device

Claims (14)

An image processing apparatus includes: a storage unit that stores a lookup table having one or two or more pieces of corresponding information, wherein the corresponding information is used to acquire all or part of one or two or more first images and The information corresponding to all or a part of the two images, and the second image is an image of the same object as the first image; the image receiving unit accepts one or two or more images; and the mapping unit uses One or two or more second images corresponding to all or a part of one or more images accepted by the image receiving unit are acquired by any one of the one or two or more pieces of correspondence information And all or a part of the image output unit outputs one or more of the one or more second images acquired by the mapping unit or one or more of the one or more second images acquired by the mapping unit Outputting an image, wherein the second image has a relationship with respect to the first image: the second image is an image obtained by another environment different from an environment in which the first image is obtained; or the first image a second image relative to the first image, the second image being a bureau Inserting an image with a shiny image; or the second image is an image that deforms the first image relative to the first image; or the second image is relative to the image a first image, the second image being an image obtained by photographing a drawing depicting the first image; or the second image being the first image relative to the first image a CG image of an image; the other environment is an environment in which the amount of light of the illumination or light source is greater than the environment, or the other environment is a position of the light source of the other environment that is clearly displayed on the image compared to the environment The environment in which the object is shadowed, or the other environment is an environment in which the position of the light source of the other environment is clearly comparable to the environment, or the environment of the object on the image is clearly perceived, or the other environment is compared to the environment The camera position of another environment can clearly show the environment of the three-dimensionality of the object on the image, or the other environment is an environment in which the illumination color is different from the environment, or the other environment is an environment different from the environment, or The other environment is temperature or Different humidity environment and the environment, or the environment for further depth to the different environments of the environment or other environment for the shutter speed and the environment different. The image processing device according to claim 1, wherein the lookup table has two or more pieces of corresponding information, and is provided with all or a part of one or more images accepted by the image receiving unit. An image analysis unit of all or a part of the corresponding first image; the mapping unit acquires the image using the corresponding information corresponding to all or a part of the first image determined by the image analysis unit A second image corresponding to all or a part of the first image determined by the analysis unit. The image processing device of claim 2, wherein all or a portion of the first image is a first space-time block of a portion of the input image; all or a portion of the second image is a second space-time block that is output to one of the images of the screen; the image receiving unit receives an image of a set of one or more images; and includes a dividing unit for receiving an image received by the image receiving unit Spatially or temporally, or spatially and temporally, the two spatial and temporal blocks are divided into two or more, and two or more first space-time blocks are obtained. The image analysis unit selects two or more first time and space according to the divided portion. Each of the blocks determines all or a part of the first image corresponding to each of the first spatiotemporal blocks; the mapping unit uses and parses the image for each of the two or more first spatiotemporal blocks a second time-space block corresponding to all or a part of the first image determined by the image analysis unit, corresponding to all or a part of the first image determined by the unit, and a synthesis unit For the 2 obtained by the mapping unit Each of the second time and space blocks is disposed in a temporal, or spatial, or spatial and temporal position of the first space-time block corresponding to the two or more second space-time blocks, and generates an output image The image output unit outputs the output image generated by the combining unit. The image processing device according to the second aspect of the invention, wherein the image analysis unit acquires one or more images received by the image receiving unit or two or more of the first ones obtained by the dividing unit. The space-time block is analyzed to obtain one or more feature quantities, and all or a part of the first image corresponding to one or more feature quantities is determined. The image processing device of claim 1, wherein the corresponding information has one or more feature quantities relating to all or a part of the first image of one object obtained in one environment; Generating a formula of all or a portion of the second image corresponding to all or a portion of the first image, or a set of parameters substituted into the formula. The image processing device according to claim 1, wherein the storage unit stores two sets of pairs of the above-mentioned type identifier for identifying the type of the lookup table and the lookup table corresponding to the type identifier; The mapping unit includes: a type identifier acquiring device that acquires a type identifier for identifying a lookup table to be used; and an output image obtaining device that uses a corresponding information of the lookup table corresponding to the type identifier All or a part of the second image corresponding to all or a part of the image accepted by the image receiving unit is obtained as any or part of the output image. The image processing device according to claim 1, further comprising: an instruction accepting unit that receives an instruction from a user; and a lookup table update unit that has two of the lookup tables in accordance with the instruction Any of the above information is changed. The image processing device according to claim 1, further comprising a restriction condition storage unit that stores a limit of a condition that the input image, the corresponding information, or the output image has one or more types of information to satisfy Condition: the mapping unit acquires all or a part of one or more images accepted by the image receiving unit so as to satisfy the restriction condition by using one of the one or more pieces of correspondence information All or part of one or more second images corresponding to each other. The image processing device of claim 1, wherein the lookup table stored in the storage unit is a lookup table obtained by a lookup table obtaining device, the lookup table obtaining device having: a first image a storage unit that stores more than one first image; a second image storage unit that stores one or more second images corresponding to the one or more first images, wherein the second image is a brain load compared to the first image An image that is adjusted to be the same object as the one or more first images; and the first image related information acquisition unit acquires all or part of the one or more first images for storage in the first One or more first image related information of all or a part of the information of one or more first images in the image storage unit; and the second image related information acquiring unit from all of the one or more second images Or a part of the second image related information obtained as information on all or a part of the one or more second images stored in the second image storage unit; and a lookup table forming unit configured to have 1 a lookup table of two or more corresponding information, the corresponding information having: the first image related information obtained by the first image related information acquiring unit, and acquired by the second image related information acquiring unit Corresponding to the second image related information of the first image related information And the correspondence information to display all of the first lines of the image over a whole or a part of the one or more second images of a portion corresponding to the information. The image processing device of claim 9, wherein the corresponding information includes: first image related information relating to all or a part of the information of the one or more first images, and is related to Second image related information of all or a part of the first image and the information corresponding to the first image related information; the lookup table obtaining device further includes: a first image related information obtaining unit, Acquiring one or more pieces of first image related information relating to information of all or a part of one or more first images stored in the first image storage unit from all or part of the one or more first images; The second image related information acquisition unit acquires information on all or a part of one or more second images stored in the second image storage unit from all or part of the one or more second images. One or more second image related information; the lookup table forming unit constituting the lookup table obtaining means constitutes a lookup table having one or two or more corresponding information, the corresponding information having: the first image related information obtained Ministry Corresponding to the first image related information and the second image related information of the information obtained by the second image related information obtaining unit and corresponding to the first image related information, and the corresponding information is displayed The 1 Information corresponding to all or a portion of the first or more first images and all or a portion of the one or more second images. The image processing device according to claim 9, wherein the correspondence information includes: a feature amount vector corresponding to all or a part of the one or more first images, and the first one or more An image conversion filter that converts all or part of the image into all or part of the one or more second images; and the lookup table configuration unit constituting the lookup table acquisition device has one or two or more corresponding information The matching table obtains the feature quantity vector from all or part of the one or more first images, and acquires all or a part of the one or more first images into the one or more second images. A conversion filter like all or part of it, and having the feature quantity vector and the conversion filter. The image processing device according to claim 9, wherein the lookup table acquisition device further includes: a second image information candidate set storage unit that stores one corresponding to each of the first images or more a plurality of second image information candidate sets, wherein the second image information candidate set is a set of candidates of two or more second image information related to information of the second image; and the candidate output unit outputs the one or more a second image information candidate set; the instruction accepting unit that selects one of the candidates for the two or more second image information included in one or more second image information candidate sets output from the candidate output unit And an instruction of the candidate for the second image information; and the second image storage unit acquires one or more second candidates by using one or more second image information candidates corresponding to the instruction received by the instruction receiving unit The image is stored in the second image storage unit in association with the first image corresponding to the second image information candidate set. An image processing method is configured to store, in a storage medium, a lookup table having one or two or more corresponding information, wherein the corresponding information is used to obtain all or a part of the first image and the second image. All or part of the corresponding information, and the second image is the first An image processing method which is realized by an image receiving unit, a mapping unit, and an image output unit, and includes an image receiving step, and the image receiving unit accepts an image. More than one image; in the mapping step, the mapping unit acquires all or a part of one or more images accepted by the image receiving step by using any one of the one or more pieces of corresponding information Corresponding to all or part of the one or more second images; and the image output step, wherein the image output unit obtains all of the one or more second images obtained by the mapping step or the mapping step One or more output images of a set of one or more second images are output, wherein the second image has the following relationship with respect to the first image: the second image is obtained and the first image is obtained An image obtained by another environment having a different image environment; or the second image is an image partially inserted with a shiny image relative to the first image; or the second image The second image relative to the first image An image obtained by deforming the first image; or the second image is an image obtained by photographing a drawing depicting the first image with respect to the first image; Or the second image is a CG image of the first image relative to the first image; the other environment is an environment in which the amount of light of the illumination or the light source is greater than the environment, or the other An environment is an environment in which the position of the light source of the other environment can clearly represent the shadow of the object on the image compared to the environment, or the environment of the other environment can be clearly displayed compared to the environment. An environment in which the object is three-dimensionally on the image, or the other environment is an environment in which the camera position of the other environment is clearly compared with the environment, or the environment of the object on the image is clearly perceived, or the other environment is an illumination color. An environment different from the environment, or the other environment is an environment different from the environment, or the other environment is an environment in which the temperature or humidity is different from the environment, or the other environment is an environment in which the depth of field is different from the environment Or other environment for the shutter speed and the environment different. A storage medium storing a lookup table having one or two or more corresponding information, wherein the corresponding information is information for obtaining all or a part of one or more first images corresponding to all or a part of the second image, And the second image is an image of the same object as the first image, so that the computer functions as the following program: The image receiving unit receives one or more images, and the mapping unit acquires one or more images accepted by the image receiving unit using any one of the one or two pieces of corresponding information. All or a part of all or a part of the corresponding one or more second images; and the image output unit outputs one or more output images, and the output image is one or more second images acquired by the mapping unit a set of one or more of the image, or a set of one or more second images obtained by the mapping unit, wherein the second image has a relationship with respect to the first image: the second image is obtained An image obtained by another environment having a different environment of the first image; or the image of the second image relative to the first image is an image partially inserted with a shiny image; or the second image The image is relative to the first image, the second image is an image obtained by deforming the first image; or the second image is a pair of images relative to the first image An image obtained by photographing the first image; or the second image is relative to a first image, the second image being a CG image of the first image; the other environment being an environment in which the amount of light of the illumination or light source is greater than the environment, or the other environment is compared to the environment The position of the light source of another environment can clearly show the environment of the object shadow on the image, or the other environment is an environment in which the position of the light source of the other environment can clearly express the stereoscopic effect of the object on the image compared with the environment. Or the other environment is an environment in which the camera position of the other environment can clearly express the stereoscopic effect of the object on the image compared to the environment, or the other environment is an environment in which the illumination color is different from the environment, or Another environment is an environment different from the environment, or the other environment is an environment in which the temperature or humidity is different from the environment, or the other environment is an environment in which the depth of field is different from the environment, or the other environment is a shutter speed A different environment than the environment.