CN1750603A - Image processing device, image recording device and image processing method - Google Patents

Abstract

The invention provides an image processing device capable of performing gray-scale transformation processing which is most suitable for a scene during the photographic process without consideration of photographic conditions, an image recording device and an image processing method. A histogram of pixel values of inputted image data is calculated in a histogram calculation part (1), and the calculated histogram is inputted into a gray-scale transformation characteristic determination part (2); a gray-scale transformation characteristic is determined from the inputted histogram in the gray-scale transformation characteristic determination part (2) referring to the photographic information; gray-scale transformation of the image data is performed according to the determined gray-scale transformation characteristic in a gray-scale transformation part (4).

Description

Image processing device, image recording device and image processing method

technical field

The present invention relates to an image processing device, an image recording device and an image processing method, and in particular to an image processing device, an image recording device and an image processing method for adaptively performing grayscale conversion processing on an image.

Background technique

The grayscale representation of an image is one of the most important factors that determine image quality. Usually, the signal output from the imaging element is approximately proportional to the light intensity incident on the imaging element. Here, the output signal from the imaging element is subjected to some kind of processing in accordance with the final image observation environment (for example, image observation by a monitor or image observation determined by printer output, etc.) in subsequent image processing. Grayscale transformation processing. For example, in the case of a general digital camera, the sRGB color space is adopted as the standard color space of the image file format, but the gradation of the image captured by the digital camera is designed so that it is most suitable for the sRGB color space with the stipulations existing in sRGB. The gradation when the monitor with the γ (gamma) characteristic (γ=2.2) in the display is displayed.

Generally, in various input devices such as a digital camera, one type of gradation transformation characteristic of an image is fixed, or the gradation transformation characteristic of an image is selected from a plurality of kinds of gradation transformation characteristics by a user or the like. In addition, in recent years, a technique of adaptively optimizing the gradation transformation characteristics for each image in accordance with the luminance distribution of the image (or scene) has been used. This is because, since the dynamic range of the subject field is different in each scene, it is difficult to change the dynamic range of an output device such as a monitor or a printer without considering the difference when transformed with a uniform gradation transformation characteristic. Efficiently reflect the brightness information of the subject in the range.

One of techniques for adaptively optimizing the gradation transformation characteristics for each image is a histogram equalization method. This method is a technique for efficiently distributing gradations to an output device by increasing the amount of luminance information contained in an image by performing gradation conversion such that the luminance histogram (frequency of each luminance gradation level) of the image becomes uniform. .

Here, if such gradation conversion is applied uniformly regardless of shooting conditions or scenes, for example, the noise in dark parts may be amplified by the gradation conversion to exceed the allowable level, and the image (scene) may move in an undesired direction. was transformed.

As an example of its solution, in the technique proposed in Patent Document 1, the brightness distribution of an image is detected, and it is determined from the detected brightness distribution whether correction of the brightness distribution is necessary, and when it is determined that correction of the brightness distribution is necessary, In this case, the performance of the output image is prevented from deteriorating by performing correction so that the luminance distribution becomes uniform.

[Patent Document 1] JP-A-2003-179809

However, in the technique proposed in Patent Document 1, since the necessity of correcting the luminance distribution is judged from the luminance distribution of the subject, for example, the scene is low in luminance and contains a lot of noise due to electrical amplification. The gradation transformation characteristics and the optimum value after gradation transformation are different depending on the conditions at the time of shooting, and it is difficult to optimize each Grayscale transformation processing.

Contents of the invention

The present invention has been made in view of the above circumstances, and an object of the present invention is to provide an image processing device and an image processing method that can perform gradation conversion processing optimal for a scene at the time of shooting regardless of shooting conditions.

In order to achieve the above object, an image processing device according to a first aspect of the present invention is an image processing device that performs image processing on an input image, and is characterized in that it includes: a histogram calculation unit that calculates pixel values of input image data a histogram; a gradation conversion characteristic determination unit that determines gradation conversion when performing gradation conversion processing on the image data based on the histogram calculated by the histogram calculation unit and information related to the input image data characteristics; and a gradation conversion processing unit that performs gradation conversion processing on the input image data based on the gradation conversion characteristics determined by the gradation conversion characteristic determination unit, and converts the gradation conversion characteristics of the image data .

In order to achieve the above object, an image recording device according to a second aspect of the present invention is an image recording device that performs image processing on an input image and records it, and is characterized in that it includes: an imaging unit that captures a subject field to obtain image data; a histogram calculation unit calculating a histogram of the pixel values of the image data obtained by the imaging unit; The photographic information determines the gradation transformation characteristic when performing gradation transformation processing on the above-mentioned image data; The data undergoes gradation conversion; and a recording unit records the image data subjected to gradation conversion by the gradation conversion unit on a recording medium.

In order to achieve the above object, an image processing method according to a third aspect of the present invention is an image processing method for performing image processing on an input image, and is characterized by having a histogram for calculating a histogram of pixel values of input image data Calculation step: determining the gradation of the gradation conversion characteristic when the gradation conversion process is performed on the image data based on the histogram calculated in the histogram calculation step and the photographing information when the image data is photographed a transformation characteristic determining step; and a gradation transformation step of performing gradation transformation on the input image data based on the gradation transformation characteristic determined in the gradation transformation characteristic determination step.

According to the first to third aspects, by considering the shooting information when the image data is obtained when determining the gradation conversion characteristics for gradation conversion, the gradation most suitable for the scene at the time of shooting can be performed regardless of the shooting conditions. Transform processing.

According to the present invention, it is possible to provide an image processing device, an image recording device, and an image processing method capable of performing gradation conversion processing optimal for a scene at the time of shooting regardless of shooting conditions.

Description of drawings

FIG. 1 is a diagram showing a conceptual configuration of an image processing device according to an embodiment of the present invention.

2 is a block diagram showing the configuration of a digital camera as an example of an image recording device including an image processing device according to an embodiment of the present invention.

FIG. 3 is a diagram showing an example of a default gradation conversion table.

FIG. 4 is a diagram showing an example of noise characteristic information.

FIG. 5 is a diagram illustrating an example of a gradation synthesis ratio.

FIG. 6 is a flowchart showing imaging control including an image processing method according to an embodiment of the present invention.

FIG. 7 is a diagram showing an example of a histogram.

FIG. 8 is a flowchart showing histogram correction processing.

FIG. 9 is a diagram showing a histogram after frequency value limitation.

FIG. 10 is a diagram showing an example of a cumulative histogram.

FIG. 11 is a flowchart showing gradation conversion table calculation processing.

FIG. 12 is a diagram showing an example of synthesis of a default gradation conversion table and a cumulative histogram.

Detailed ways

Embodiments of the present invention will be described below with reference to the drawings.

FIG. 1 is a diagram showing a conceptual configuration of an image processing device according to an embodiment of the present invention.

As shown in FIG. 1 , the present image processing device is composed of a histogram calculation section 1 , a gradation transformation characteristic determination section 2 , and a gradation transformation section 4 . When image data is input to the histogram calculation section 1 , a histogram of pixel values of the input image data is calculated in the histogram calculation section 1 . Regarding the histogram, a histogram of only the brightness component of the image data (brightness histogram) may be calculated, or a histogram of each color component of the image data may be calculated.

After the histogram is calculated in the histogram calculation unit 1 , the calculated histogram is input to the gradation transformation characteristic determination unit 2 . In the gradation transformation characteristic determining unit 2 , the gradation transformation characteristic is determined based on the histogram and the photographing information 3 when the image data is photographed. Then, based on the determined gradation conversion characteristics, in the gradation conversion unit 4 , the gradation conversion processing of the input image data is performed, and output as output image data to the outside.

Hereinafter, the image processing device of FIG. 1 will be described more specifically. 2 is a block diagram showing a configuration of a digital camera (hereinafter referred to as a camera) as an example of an image recording device including an image processing device according to an embodiment of the present invention.

As shown in Fig. 2, this digital camera is made up of following parts: Microcomputer 11; Camera section 12; A/D conversion section (marked as A/D in the figure) 13; Bus 14; RAM15; Image processing circuit 16 ; ROM 17 ; recording medium 18 ; and operation unit 19 .

The microcomputer 11 is a control unit for overall control of the camera. The microcomputer 11 performs focus control of the imaging optical system inside the imaging unit 12 , exposure control of the imaging element, recording control when recording image data on the recording medium 18 , and the like.

The imaging unit 12 is constituted by an imaging optical system or an imaging element, a drive unit for these parts, and the like. The imaging unit 12 converts, in an imaging element, a light beam from a subject (not shown) incident through the imaging optical system into an electrical signal.

The A/D conversion unit 13 converts the electrical signal obtained by the imaging unit 12 into digital data to generate image data.

The bus 14 is a transmission path for transmitting data such as image data obtained by the A/D conversion unit 13 to each circuit of the camera. In addition, RAM 15 is a memory for temporarily storing data such as image data.

The image processing circuit 16 is a circuit that performs image processing on input image data input via the bus 14 . Here, the image processing circuit 16 is composed of the following parts: a white balance (WB) correction unit 20; a synchronization unit 21; a Y/C separation unit 22; a color conversion unit 23; a JPEG compression unit 24; Histogram correction unit 26 ; histogram accumulation unit 27 ; gradation conversion table calculation unit 28 and gradation conversion unit 29 . Here, the gradation conversion characteristic determination unit 2 corresponds to the histogram calculation unit 25 , the histogram correction unit 26 , the histogram accumulation unit 27 , and the gradation conversion table calculation unit 28 .

The ROM 17 serving as a noise characteristic storage unit and a fixed gradation conversion characteristic storage unit is a memory for storing various control programs executed by the microcomputer 11 and various setting values of the camera. In particular, the default gradation conversion table 30, noise characteristic information 31, and gradation synthesis ratio 32 are stored in the ROM 17 of the present embodiment.

The default gradation conversion table 30 is a gradation conversion table having standard characteristics stored as fixed characteristics for each camera in the ROM 17 . An example of the default gradation conversion table 30 is shown by a solid line in FIG. 3 . Here, the horizontal axis in FIG. 3 represents image input values. Note that the image input values in FIG. 3 are pixel values of the image data input from the A/D conversion unit 13 . In addition, the vertical axis on the left side of FIG. 3 represents the output value (8-bit output) after gradation conversion. In addition, the default gradation conversion table stored in ROM 17 is not limited to one. For example, a plurality of different default grayscale conversion tables may also be stored in advance, and the user may arbitrarily select the default grayscale conversion table. Alternatively, an optimal default gradation conversion table may be automatically selected from a plurality of default gradation conversion tables according to photographing conditions.

The noise characteristic information 31 is information on noise characteristics, and indicates to what extent and in what form noise is added to the image when the image is captured. The noise characteristic information 31 is information stored in the ROM 17 as a fixed value. The noise characteristic information 31 is shown by a solid line in FIG. 4 . Here, the horizontal axis in FIG. 4 represents input values. The input value here is an A/D conversion value in the A/D conversion unit 13 as in FIG. 3 . In addition, the vertical axis on the left side of FIG. 4 represents the amount of noise. As shown in Figure 4, if the input value increases, the amount of noise also increases. Also, in Fig. 4, there is noise even when the input value is 0, but this is a dark current component.

Here, the noise characteristic information 31 is an amount that changes with imaging sensitivity, temperature, exposure time, and the like during imaging. For example, when the photographing sensitivity at the time of photographing is high, the amount of noise increases. Therefore, a plurality of pieces of noise characteristic information corresponding to changes in imaging sensitivity, temperature changes, and exposure time may be stored in the ROM 17 in advance, and the information corresponding to the imaging sensitivity, temperature, and exposure time at that time may be read out when image data is captured. noise characteristic information.

In addition, in recent years, cameras having a noise reduction processing function for reducing image noise during shooting have also been proposed, so the ROM 17 may also store noise in a state where noise reduction processing has been performed corresponding to this. property information.

The gradation combination ratio 32 is a combination ratio when combining the default gradation conversion table 30 and the cumulative histogram described later. An example of the gradation synthesis ratio 32 is shown in FIG. 5 . As shown in FIG. 5, the gradation composite ratio 32 stores a value corresponding to the scene mode. Here, the scene mode is one of shooting modes for shooting with various settings, and is a mode in which a scene at the time of shooting can be set. By setting the scene mode, a setting value suitable for each scene can be automatically selected for exposure control and the like. In this embodiment, as the gradation composite ratio corresponding to the scene mode, for example, a standard mode for shooting with standard settings, a landscape mode for shooting with settings suitable for landscape shooting, and a landscape mode for shooting with settings suitable for landscape shooting are stored, for example. The setting for portrait photography performs the grayscale synthesis ratio corresponding to the portrait mode for photography and the night scene mode for photography with settings suitable for nightscape photography, but is not limited thereto.

The recording medium 18 is a recording medium on which images processed by the image processing circuit 16 are recorded, and is constituted by, for example, a memory card or the like.

The operation unit 19 is various operation members operated by a user. When the operation unit 19 is operated by the user, various controls are performed by the microcomputer 11 according to the operation state. Here, the operation unit 19 includes, for example, a shutter button for instructing to execute shooting, a selection button for selecting a scene mode, and the like.

Referring to FIG. 6 , shooting control in the camera having the configuration shown in FIG. 2 will be described. FIG. 6 is a flow chart showing a procedure of imaging control including an image processing method according to an embodiment of the present invention. Here, the flowchart of FIG. 6 is started when the user performs an ON operation of the shutter button.

When the shutter button is turned on by the user, well-known AE and AF are performed based on the output of the imaging unit 12 (step S1). Thereafter, exposure control is performed (step S2 ), and an image signal for recording can be obtained in the imaging unit 12 . Thereafter, imaging processing is performed on the image signal for recording obtained in the imaging unit 12 (step S3). In this imaging process, the A/D converting unit 13 performs A/D conversion on the image signal obtained by the imaging unit 12 . The image data obtained by the A/D conversion unit 13 is input to the WB correction unit 20 of the image processing circuit 16 .

White balance correction of the image data is performed in the WB correction unit 20 (step S4). In the white balance correction, the R gain and the B gain of the image data are corrected so that the white of the image input to the WB correcting section 20 becomes appropriate. The image data whose white balance has been corrected in the WB correction unit 20 is input to the synchronization unit 21 .

Synchronization processing is performed in the synchronization unit 21 (step S5). In the synchronization processing, image data having three RGB colors as one pixel component is generated from the image data input to the synchronization unit 21 by interpolation. The image data synchronized by the synchronization unit 21 is input to the Y/C separation unit 22 .

Y/C separation processing is performed in the Y/C separation unit 22 (step S6). In the Y/C separation process, the input image data is separated into a Y (brightness) signal and a C (color) signal. The Y signal among the separated signals is input to the histogram calculation unit 25 and the gradation conversion unit 29 , and the C signal among the separated signals is input to the color conversion unit 23 .

Color conversion processing is performed in the color conversion unit 23 (step S7). In the color conversion process, the C signal input to the color conversion unit 23 is converted into a standard color signal such as sRGB by a camera or the like. The signal subjected to the color conversion process in the color conversion unit 23 is input to the JPEG compression unit 24 .

A histogram calculation process is performed in the histogram calculation unit 25 (step S8). A histogram (brightness histogram) is calculated from the frequency value of each luminance input of the Y signal input to the histogram calculation section 25 in the histogram calculation process. An example of the histogram calculated by the histogram calculation unit 25 is shown by a solid line in FIG. 7 . Here, the horizontal axis in FIG. 7 represents the luminance input value. In addition, the vertical axis on the left side of FIG. 7 represents the luminance distribution, that is, the frequency value of luminance input. The histogram calculated by the histogram calculation unit 25 is input to the histogram correction unit 26 .

In addition, in this embodiment, the histogram is calculated from the luminance component of the image data, but the histogram of the color component of the image data may also be calculated. In this case, the histograms of all three RGB colors may be calculated, or the histograms of only the G component may be calculated.

The histogram correction process is performed in the histogram correction part 26 (step S9). In the histogram correction process, the histogram calculated by the histogram calculation unit 25 is corrected based on the noise characteristic information 31 stored in the ROM 17 .

The histogram correction processing will be described with reference to FIG. 8 . In the histogram correction process, first, the default gradation conversion table 30 stored in the ROM 17 is read (step S21). Next, calculate the slope of the default gradation conversion table 30 (step S22). Here, the slope of the default grayscale conversion table 30 can be obtained by differentiating the default grayscale conversion table 30 . For example, when the default gradation conversion table 30 is shown by the solid line in FIG. 3 , its slope is shown by the dotted line in FIG. 3 .

After calculating the slope of the default gradation conversion table 30, the noise characteristic information 31 stored in the ROM 17 is read (step S23). Second, the amount of noise after the grayscale transformation is inferred. The noise amount after gradation conversion is the product of the noise amount and the amplification factor of the noise after gradation conversion. Here, the slope of the default gradation conversion table 30 calculated in step S22 represents the amplification factor of noise after gradation conversion. Therefore, the amount of noise after grayscale transformation becomes the product of the noise amount shown by the solid line in FIG. 4 and the slope of the default grayscale transformation table shown by the dotted line in FIG. The subsequent noise amount becomes the noise amount shown by the dotted line in FIG. 4 . As shown by the dotted line in FIG. 4 , the peak of the amount of noise appears in the dark portion of the original image after the gradation conversion. This is because the dark part of the original image is stretched and the bright part is compressed by the gradation transformation.

After estimating the amount of noise after gradation conversion, the histogram frequency limit level is determined in order to correct the histogram (step S24). Here, in this embodiment, the frequency value of the histogram is limited so that noise after gradation conversion becomes inconspicuous. For this reason, the reciprocal of the noise amount after gradation transformation is calculated as the frequency value limit level. This frequency value limit level is shown in the dotted line in FIG. 7 . As shown in FIG. 7 , the restriction level of the frequency value becomes larger in a portion where the amount of noise after gradation conversion becomes larger.

Here, in this embodiment, the frequency limit level of the histogram is set to the reciprocal of the amount of noise after gradation conversion, but for example, a predetermined calculation may be performed after calculating the reciprocal to obtain a more appropriate frequency value. degree limit level.

After the frequency value limit level is determined, the portion exceeding the frequency value limit level in the histogram is limited as shown in FIG. 9 (step S25). By performing gradation conversion using the histogram corrected in this way, noise after gradation conversion becomes inconspicuous.

Here, return to the description of FIG. 6 . The histogram corrected by the histogram correction unit 26 is input to the histogram accumulation unit 27 . In the histogram accumulation unit 27, a histogram accumulation process is performed (step S10). In the histogram accumulation processing, the histograms input to the histogram accumulation section 27 are accumulated sequentially from the low luminance component side.

An example of a cumulative histogram is shown in FIG. 10 . Here, the solid line in FIG. 10 shows the cumulative histogram before the histogram is corrected by the histogram correction unit 26 . In addition, the dotted line in FIG. 10 shows the cumulative histogram after the histogram correction was performed in the histogram correction unit 26 . However, the corrected cumulative histogram of the histogram is normalized so that the maximum value of cumulative frequencies (corresponding to the total number of frequencies) coincides with the maximum value of cumulative frequencies before histogram correction. In the cumulative histogram after the histogram correction, the slope of the part where the amount of noise increases after the gradation conversion becomes gentler than that in the cumulative histogram before the histogram correction.

The cumulative histogram obtained in the histogram accumulation unit 27 is input to the gradation conversion table calculation unit 28 . The gradation conversion table calculation process is performed in the gradation conversion table calculation unit 28 (step S11).

Referring to Fig. 11, the gradation conversion table calculation process will be described. In the gradation conversion table calculation process, the cumulative histogram obtained by the histogram accumulation unit 27 and the default gradation conversion table 30 stored in the ROM 17 are combined at a predetermined combination ratio to calculate the gradation conversion table.

In FIG. 11, first, the scene mode information at the time of shooting is checked (step S31). Next, based on the scene mode information verified in step S31, it is judged which ratio of the gradation synthesis ratios stored in the ROM 17 should be selected (step S32). Next, synthesize the default grayscale conversion table 30 and the cumulative histogram according to the judged grayscale synthesis ratio (step S33 ).

An example of synthesis of the default gradation conversion table 30 and the cumulative histogram is shown in FIG. 12 . Here, the thin solid line in FIG. 12 shows the default grayscale conversion table, the dotted line in FIG. 12 shows the cumulative histogram, and the thick solid line in FIG. 12 shows the final grayscale conversion table obtained after synthesis. In addition, in the example of FIG. 12, the scene mode is the standard mode (gradation synthesis ratio 0.5:0.5). That is, in the example of FIG. 12 , since the grayscale synthesis ratio is 0.5:0.5, the grayscale conversion table obtained after synthesis is the average value of the default grayscale conversion table 30 and the cumulative histogram.

Also, although not shown in FIG. 12 , when photographing a high-contrast subject such as a landscape, more appropriate gradation expression can be performed by increasing the ratio of one side of the cumulative histogram. Conversely, in the case of a person, the original subject has low contrast, and the default gradation conversion table is important in order to prevent the contrast from becoming more than necessary. Furthermore, in the case of a night scene, the ratio of the default gradation conversion table is increased so that an originally dark image is not brightened more than necessary. In addition, in the case of a night scene, the combination of the default gradation conversion table and the cumulative histogram may not be performed.

Note that the grayscale composition ratio is not limited to storing only the value corresponding to the scene mode, for example, the grayscale composition ratio corresponding to the setting of the flash mode or the automatic exposure mode may also be stored in advance. For example, when shooting with a flash, since the contrast of the image is increased, it is only necessary to increase the ratio of one side of the cumulative histogram as in the landscape scene to perform gradation synthesis. Also, in the case of manual exposure, compositing may be prohibited. In addition, gradation composition corresponding to whether or not the noise reduction processing function is used may be performed. That is, when noise reduction processing is performed, the ratio of the default gradation conversion table is increased.

Here, return to the description of FIG. 6 . The gradation conversion table calculated by the gradation conversion table calculation unit 28 is input to the gradation conversion unit 29 . The gradation conversion process is performed in the gradation conversion unit 29 (step S12). In the gradation conversion process, the Y signal input from the Y/C separation unit 22 is subjected to gradation conversion based on the gradation conversion table input from the gradation conversion table calculation unit 28 . The gradation-converted Y signal is input to the JPEG compression unit 24 .

In the JPEG compression unit 24, JPEG compression is performed on the grayscale-converted Y signal and the color-converted C signal (step S13). Thereafter, an image file is created by adding header information such as the photographing information to the JPEG-compressed data (step S14), and the created image file is recorded on the recording medium 18 (step S15). Thus, the imaging control ends. By recording the shooting information in the header information of the image file in advance, the gradation conversion process described in this embodiment can also be performed in the post-processing.

As described above, according to the present embodiment, when calculating the gradation conversion table at the time of gradation conversion, since the scene information at the time of shooting can be reflected, the gradation conversion process most suitable for the shooting scene can be performed.

As mentioned above, although this invention was demonstrated based on embodiment, this invention is not limited to said embodiment, It goes without saying that various deformation|transformation and application are possible within the range of the summary of this invention. For example, the above-mentioned one embodiment has been described only for image capturing, but the technique of the present invention can also be applied for image reproduction.

In addition, in the above-mentioned one embodiment, the case where all the same gradation transformations are performed in one screen is described, but one screen may be divided into multiple areas, and each divided area may be used Different conditions are used to calculate the gray scale transformation table.

In addition, inventions at various stages are included in the above-described embodiments, and various inventions can be extracted by appropriate combinations of a plurality of disclosed constituent elements. For example, even if some constituent elements are deleted from all the constituent elements shown in the embodiments, the problems described in the column of the problems that the invention intends to solve can be solved, and the effects described in the column of the effects of the invention can be obtained. In the case of , the structure in which the constituent elements are deleted can also be extracted as an invention.

Claims (11)

1. one kind is carried out the image processing apparatus of image processing for input picture, it is characterized in that possessing:

Histogram calculation portion, the histogram of the pixel value of the view data that calculating has been transfused to;

Greyscale transformation characteristic determination section, the photographic information when having carried out photography, the greyscale transformation characteristic when decision is carried out greyscale transform process to above-mentioned view data according to the above-mentioned histogram that has calculated by above-mentioned histogram calculation portion with to above-mentioned view data; And

Greyscale transformation portion is according to by the determined above-mentioned greyscale transformation characteristic of above-mentioned greyscale transformation characteristic determination section the above-mentioned view data that has been transfused to being carried out greyscale transformation.

2. the image processing apparatus described in claim 1 is characterized in that,

When also being included in the above-mentioned greyscale transformation characteristic of decision, above-mentioned greyscale transformation characteristic determination section revises the above-mentioned histogrammic histogram modification portion of having calculated with above-mentioned histogram calculation portion according to above-mentioned photographic information.

3. the image processing apparatus described in claim 2 is characterized in that,

The photographic information that is used when above-mentioned histogrammic revise comprises whether photography sensitivity information when view data carried out photography and expression carried out reducing the reduction noise processed information of noise processed to view data some at least information.

4. the image processing apparatus described in claim 2 is characterized in that,

Also possess the noise characteristic storage part of storage about the information of above-mentioned noise in image data characteristic,

Above-mentioned greyscale transformation characteristic determination section is when above-mentioned histogrammic correction, read the information of the noise characteristic when above-mentioned view data having been carried out photography according to above-mentioned photographic information from above-mentioned noise characteristic storage part, according to the information of this noise characteristic when above-mentioned view data having been carried out photography that has been read out, limit the frequency value of above-mentioned histogrammic specific part.

5. the image processing apparatus described in claim 4 is characterized in that,

Also possess at least a kind of fixedly greyscale transformation characteristic storage part that can use and have the fixedly greyscale transformation characteristic of fixing characteristic without exception to above-mentioned view data of storage,

Above-mentioned greyscale transformation characteristic determination section also carries out following work: when above-mentioned histogrammic correction, the information of the noise characteristic when above-mentioned view data having been carried out photography of having read according to the said fixing greyscale transformation characteristic that has been stored in said fixing greyscale transformation characteristic storage part with from above-mentioned noise characteristic storage part determines the limit amount of above-mentioned frequency value.

One kind for input picture carry out image processing and the record image recording structure, it is characterized in that possessing:

Image pickup part is made a video recording to obtain view data to being shot;

The histogram of the pixel value of the view data that is obtained by above-mentioned image pickup part calculates in histogram calculation portion;

Greyscale transformation characteristic determination section, the photographic information when having carried out photography, the greyscale transformation characteristic when decision is carried out greyscale transform process to above-mentioned view data according to the above-mentioned histogram that has calculated by above-mentioned histogram calculation portion with to above-mentioned view data;

Greyscale transformation portion is according to by the determined above-mentioned greyscale transformation characteristic of above-mentioned greyscale transformation characteristic determination section the above-mentioned view data that has been transfused to being carried out greyscale transformation; And

Recording portion, the view data that record has carried out greyscale transformation by above-mentioned greyscale transformation portion on recording medium.

7. one kind is carried out the image processing method of image processing for input picture, it is characterized in that having:

Calculate the histogrammic histogram calculation operation of the pixel value of the view data that has been transfused to;

The greyscale transformation characteristic decision operation of the greyscale transformation characteristic the when photographic information when having carried out photography according to the above-mentioned histogram that has been calculated in the above-mentioned histogram calculation operation with to above-mentioned view data decides above-mentioned view data carried out greyscale transform process; And

According to the greyscale transformation operation of in above-mentioned greyscale transformation characteristic decision operation, the above-mentioned view data that has been transfused to being carried out greyscale transformation by determined above-mentioned greyscale transformation characteristic.

8. the image processing method described in claim 7 is characterized in that,

The above-mentioned histogrammic histogram modification operation of having been calculated in above-mentioned histogram calculation operation according to above-mentioned photographic information correction when above-mentioned greyscale transformation characteristic decision operation is included in the above-mentioned greyscale transformation characteristic of decision.

9. the image processing method described in claim 8 is characterized in that,

The photographic information that is used in above-mentioned histogram modification operation comprises whether photography sensitivity information when view data carried out photography and expression carried out reducing the reduction noise processed information of noise processed to view data some at least information.

10. the image processing method described in claim 8 is characterized in that,

Limit the frequency value of above-mentioned histogrammic specific part by information, carry out the above-mentioned histogrammic correction in the above-mentioned histogrammic correction operation according to the noise characteristic when above-mentioned view data having been carried out photography.

11. the image processing method described in claim 10 is characterized in that:

In above-mentioned histogram modification operation, also carry out following work: the limit amount that decides above-mentioned frequency value according to the information of the fixedly greyscale transformation characteristic that can use and have fixing characteristic to above-mentioned view data without exception and the noise characteristic when above-mentioned view data having been carried out photography.

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