JP4359730B2 - Monotone conversion apparatus, monotone conversion method, and medium recording monotone conversion program - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a monotone conversion apparatus that converts a color image into a monotone image, a monotone conversion method, and a medium on which a monotone conversion program is recorded.
[0002]
[Prior art]
In recent years, digital still cameras have begun to be used rapidly. When the image is taken with a digital still camera, the image can be managed as data, and image processing can be easily performed. For example, a color image can be converted into a monotone image such as black and white or sepia.
Conventionally, such conversion to monotone has been performed by simply replacing the data with a monotone while maintaining the luminance for each pixel in the dot matrix form.
[0003]
[Problems to be solved by the invention]
In the above-described conventional monotone conversion device, the quality of the image when the monotone conversion is performed is not so much questioned, and as a result, there is a problem that the original luminance distribution is converted as it is.
The present invention has been made in view of the above problems, and provides a monotone conversion device, a monotone conversion method, and a medium on which a monotone conversion program is recorded, which can improve the quality of an image even in the case of monotone conversion. Objective.
[0004]
[Means for Solving the Problems]
  To achieve the above purpose, PaintingAn image acquisition means for expressing an image as each pixel of a dot matrix and obtaining gradation data for each pixel with a predetermined element color obtained by color separation, and a luminance equivalent value of each pixel based on the image data Luminance distribution aggregation means for performing aggregation, luminance correspondence setting means for deriving a correspondence relationship of luminance conversion for changing the luminance distribution based on the aggregated luminance distribution, and based on the derived correspondence relationship of luminance conversion Image data conversion means for generating monotone image data obtained by converting the luminance of each pixel in the image data.Also good.
[0005]
  the aboveConstitutionIn this case, when the image acquisition means acquires the image data representing the image as each pixel in a dot matrix and expressing the gradation for each pixel with a predetermined element color obtained by color separation, the luminance distribution aggregation means is based on the image data. The luminance correspondence value setting means derives the correspondence relationship of the luminance conversion for changing the luminance distribution based on the aggregated luminance distribution, so that the image data conversion means is derived Monotone image data obtained by converting the luminance of each pixel in the image data based on the correspondence relationship of the luminance conversion is generated.
  The present invention provides an image acquisition means for acquiring image data that represents an image as each pixel in a dot matrix and represents a gradation for each pixel with a predetermined element color that has been color-separated, and each pixel based on the image data. A luminance distribution totaling unit for totaling the luminance equivalent values and a luminance conversion table for changing the luminance distribution by converting the luminance equivalent values are derived based on the aggregated luminance distributions, and the luminance equivalent values are set to a predetermined value. Set a conversion table for each element color to convert to element colors that express a monotone of color tone, and generate an integrated conversion table for each element color by integrating the luminance conversion table into each conversion table for each element color Each of the integrated conversion tables for each element color is input with a luminance equivalent value of each pixel in the image data. By conversion result by table to obtain the tone values of element colors of each pixel is a structure comprising an image data converting means for obtaining image data of the monotone of the predetermined color tone.
[0006]
In other words, the distribution of luminance equivalent values (meaning luminance or a value that is not exact but equivalent to luminance) for each pixel constituting the image is obtained, and if there is room for improvement in this luminance distribution, luminance conversion is supported. A relationship is derived, and a monotone image in which the luminance of each pixel is converted is generated based on the relationship. More specifically, conversion is performed so that the color of each pixel becomes monotone while setting the luminance of a certain pixel to an appropriate luminance.
Conversion of image data to monotone is used in various fields. For example, monotone conversion is prepared as one option when a digital image is input to a photo retouching software of a computer and a desired filtering process is performed on the software. Also, the digital still camera itself may be provided with monotone conversion called sepia tone photography. Accordingly, the image acquisition means may be any device that can acquire color image data, such as a specific image sensor such as a CCD, an external device such as a scanner, or a data line. There is no particular limitation such as merely supplying image data. Further, even when the image data is already prepared in a state where it is developed on the memory, this corresponds to acquiring the image data at the time of reading from the memory.
[0007]
  The monotone here is not necessarily limited to black and white, and even a so-called single colored expression is a monotone. As an example of monotone conversion,UpThe luminance correspondence setting means is a configuration for setting the correspondence for changing the luminance distribution with the luminance equivalent value and setting the correspondence with the composition ratio between the element colors after the luminance change as a predetermined ratio.Also good.
[0008]
  the aboveConstitutionIn FIG. 5, after changing the luminance distribution with the luminance equivalent value, the component ratio between the element colors is set to a predetermined ratio. In other words, since the composition ratio between the component colors in the monotone image data is a predetermined ratio, it is colored monotone image data such as sepia.
  However, when the component ratio between the element colors here is the same, it becomes monochrome image data. This is because in order to represent black and white with a plurality of element colors, it is only a result of giving the same gradation value for each component.
  The present invention further includes means for acquiring a coloring instruction for instructing a monotone color tone in response to an external input, and the table setting means expresses a luminance equivalent value and a monotone of a color indicated by the acquired coloring instruction. The luminance conversion table may be integrated with the conversion table for each element color that defines the conversion relationship with the element color to be processed.
[0009]
It should be noted that it is complicated to obtain the optimum gradation value for each gradation value individually when deriving the correspondence. Therefore, a conversion table may be generated based on the tone curve for collectively determining the correspondence relationship, and conversion may be performed using this conversion table when converting from the original luminance to the corrected luminance. Of course, this tone curve represents the correspondence based on the luminance distribution. For example, if the result of obtaining the luminance distribution seems to be dispersed in a dark region as a whole, it is moved to the bright side as a whole, but at this time, it is uniquely determined by a certain parameter such as a γ curve. The curve is used as the tone curve, and only this parameter is determined. As a result, the conversion value corresponding to each gradation value is determined by the tone curve regardless of the width of the gradation value.
Note that the tone curve is not limited to the case where the tone curve is provided only in one direction, and can be appropriately changed such as an S shape.
[0010]
  Even when the composition ratio between the element colors is set to a predetermined ratio, there are various methods for realizing it, and the present invention is not limited to a case where the ratio is constant over all gradation values. As an example,UpThe luminance correspondence relationship setting means uses a tone curve to achieve a constant composition ratio at a certain luminance value and smooth over all gradation values when setting the composition ratio between each element color to a predetermined ratio after the brightness change. As a configuration to changeAlso good.
  Further, according to the present invention, the table setting means has a constant configuration with a certain luminance equivalent value as a conversion table for each element color in which the composition ratio between the element colors is a ratio for expressing the monotone of the predetermined color tone. The tone curve is used to smoothly change the conversion result over all gradation values while realizing the ratio.
[0011]
  If a constant ratio is set over all gradation values, it can be realized at a constant ratio when the luminance value is close to “0”, but it is difficult to realize the constant ratio when the gradation value is close to the maximum value. Therefore, by using a tone curve that realizes a typical composition ratio at a certain luminance value and the difference converges on the end side, it is smoothly changed over all gradation values, and the above-mentioned problem is solved.
  As an example of a method for generating monotones,UpThe luminance correspondence relationship setting means is configured to set a correspondence relationship that collectively changes the luminance distribution with the luminance equivalent value and the conversion that changes the component ratio between the element colors to a predetermined ratio after the luminance change.Also good.
[0012]
In order to make the composition ratio of each element color a predetermined ratio while the brightness is finally corrected to an appropriate value, the correspondence relationship of the monotone conversion with the brightness relative value is once derived conceptually. It is also possible to take two steps, such as converting the luminance in black and white, and changing the composition ratio between the element colors in a state where the luminance value in black and white is converted. However, as long as the gradation value is limited, it is possible to realize a two-stage correspondence at a time by obtaining a result of two-stage correspondence in advance.
[0013]
  As an example of setting multiple levels of correspondence in this way,UpThe luminance correspondence setting means generates a conversion table corresponding to each of the individual correspondences, and integrates this conversion table to generate an integrated conversion table.Also good.
  A conversion table representing each correspondence relationship is generated in advance, and the conversion table is referred to in a plurality of stages while changing the luminance value of the conversion source over all gradation values. Then, by setting the result as a luminance value after conversion with respect to the luminance value of the conversion source, an integrated integrated conversion table can be easily realized.
[0014]
The integration of conversion tables is not limited to coloring. For example, first, when the corresponding correspondence of the luminance conversion is derived individually from the aggregated luminance distribution based on a plurality of elements, and then the integrated correspondence that sequentially adapts each correspondence is derived. Generates a conversion table representing the integrated correspondence. For example, the correspondence relationship for improving contrast and the correspondence relationship for improving brightness are not exclusive, and an integrated correspondence relationship is derived in order to realize both correspondence relationships.
[0015]
In this case, first, a conversion table corresponding to each correspondence relationship is generated, and then this conversion table is integrated to generate an integrated conversion table. That is, the next conversion table is referenced using a value referenced in a certain conversion table, and the referenced value is made to correspond to the first value. Of course, the number of conversion tables to be referred to is not limited to two, and an arbitrary number of conversion tables can be integrated.
By the way, when obtaining the luminance of each pixel with respect to color image data, it is often difficult to obtain a luminance having a strict meaning. That is, if the coordinate system used by the image data does not employ a single luminance parameter, the coordinate system must be converted, but strictly speaking, there is often no linear correspondence between the coordinate systems. . In this case, if the correspondence is obtained by calculation, the amount of computation increases, and if a conversion table in which the correspondence is derived in advance is used, depending on the number of colors that can be reproduced, the table becomes extremely large. turn into.
[0016]
However, what is used is a result of the aggregation of the luminance distribution, and it is not always necessary to have a strict luminance. For this reason, the luminance distribution aggregation means does not perform strict luminance conversion, but derives the luminance by linear conversion from the gradation values of each element color so that it can be done with relatively simple processing. You may make it ask. In addition, the linear transformation here can be interpreted broadly. For example, it is only necessary to be able to be obtained by a simplified calculation except when it cannot be derived without referring to a table or when a high-load calculation process must be performed by a non-linear calculation.
[0017]
  Further, it is meaningful to take a step of improving the luminance distribution after obtaining it, and the specific points to improve are not particularly limited. However, as an exampleThe table aboveThe setting unit converts the range from the maximum luminance to the minimum luminance derived based on the luminance distribution as the contrast width, and converts the contrast width from the original luminance to the corrected luminance so as to be an appropriate width.Brightness conversion tableIs derived.
[0018]
  the aboveConstitutionIn, the range from the maximum luminance to the minimum luminance derived based on the luminance distribution is regarded as the contrast width. When the range from the maximum luminance to the minimum luminance is narrow, the available contrast width is not effectively used. For this reason, by deriving a correspondence relationship that expands the width of contrast, the width of contrast becomes wider when converted from the original luminance to the modified luminance. Theoretically, the reverse is also possible.
[0019]
  As another exampleThe table aboveThe setting means converts from the original luminance to a modified luminance so that the luminance distribution becomes an appropriate distribution as a whole when the brightness of the image derived based on the luminance distribution is not in an appropriate range.Brightness conversion tableIs derived.
  the aboveConstitutionIn, the brightness of the image is determined from the luminance distribution. That is, if the luminance distribution is concentrated in a bright area, it can be determined that it is too bright, and if it is concentrated in a dark area, it can be determined that it is too dark. Therefore, the brightness of the image can be adjusted by making it as biasless as possible. For this reason, a correspondence relationship is derived so that the luminance distribution is an appropriate distribution as a whole. For example, if the mountain in the frequency distribution is biased to a dark area, the mountain is moved around the center of all gradations. Conversely, if the mountain is biased to a bright area, the mountain is similarly shifted to the center of all gradations. A correspondence relationship that is moved around is derived.
[0020]
As described above, if there is room for improving the luminance distribution, the method of deriving the correspondence relationship of the luminance conversion and converting the luminance is not necessarily limited to a substantial device, and it is easy to function as that method. Can understand. That is, it is not necessarily limited to a substantial apparatus, and there is no difference that the method is also effective.
In addition, the monotone conversion device may exist alone or may be used in a state where it is incorporated in a certain device. The idea of the invention is not limited to this and includes various aspects. . Therefore, it can be changed as appropriate, such as software or hardware.
[0021]
When the software of the monotone conversion device is embodied as an embodiment of the idea of the invention, it naturally exists on a recording medium on which such software is recorded, and it must be used.
Of course, the recording medium may be a magnetic recording medium, a magneto-optical recording medium, or any recording medium that will be developed in the future. In addition, the duplication stages such as the primary duplication product and the secondary duplication product are equivalent without any question. In addition, even when the communication method is used as a supply method, the present invention is not changed.
[0022]
Further, even when a part is software and a part is realized by hardware, the idea of the invention is not completely different, and a part is stored on a recording medium and is appropriately changed as necessary. It may be in the form of being read. Needless to say, the present invention is realized by the program itself.
[0023]
【The invention's effect】
As described above, the present invention adjusts the luminance of each pixel so as to obtain an optimal luminance distribution, and thus can provide a monotone conversion device capable of generating a monotone image with good image quality.
[0024]
  Also,BookAccording to the invention, each element color can be obtained so as to have a predetermined composition ratio while obtaining an optimal luminance distribution, and a monotone conversion of a desired color including black and white can be realized.
  further,BookAccording to the invention, since the change in the composition ratio is realized by the tone curve, the value of each element color can be obtained relatively easily.
  further,BookAccording to the invention, since the conversion in a plurality of stages is realized at once, the processing can be speeded up.
[0025]
  further,BookAccording to the invention, it is possible to realize a correspondence that is simply integrated using a conversion table.
  further,BookAccording to the invention, it is possible to generate a monotone image with an appropriate contrast width.
  further,BookAccording to the present invention, it is possible to generate a monotone image having an appropriate range of brightness, that is, an appropriate brightness without being too bright or too dark.
[0026]
  further,BookAccording to the invention, a monotone conversion method having the same effectandA medium recording a monotone conversion program can be provided.
[0027]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, embodiments of the present invention will be described with reference to the drawings.
FIG. 1 shows a monotone conversion apparatus according to an embodiment of the present invention by a schematic diagram corresponding to claims, and FIG. 2 shows a computer system 10 as an example of hardware for realizing the monotone conversion apparatus by a block diagram. Yes. First, the computer system 10 will be described.
[0028]
The computer system 10 includes a scanner 11a, a digital still camera 11b, and a video camera 11c as image input devices for directly inputting image data, and these are connected to the computer main body 12. Each input device can generate image data in which an image is expressed by a dot matrix pixel and output the image data to the computer main body 12. Here, the image data is displayed in 256 gradations for each of the three primary colors of RGB. About 16.7 million colors can be expressed. Various types of image data formats are used, including a compressed JPEG format and an uncompressed BMP format.
[0029]
A floppy disk drive 13a, a hard disk 13b, and a CD-ROM drive 13c as external auxiliary storage devices are connected to the computer main body 12, and main programs related to the system are recorded on the hard disk 13b. Necessary programs and the like can be read from a CD-ROM or the like and recorded on the hard disk 13b.
In addition, a modem 14a is connected as a communication device for connecting the computer main body 12 to an external network or the like, and it can be connected to an external network via the public communication line, and can be installed by downloading software and data. It has become. In this example, the modem 14a accesses the outside via a telephone line, but it is also possible to adopt a configuration where the network is accessed via a LAN adapter.
[0030]
Here, among the external auxiliary storage devices, the floppy disk drive 13a and the CD-ROM drive 13c can be replaced by the recording medium itself, and supplied with the image data recorded on the recording medium. It can also be a means of an image input device. Further, when a network is accessed via the modem 14a or the LAN adapter, image data may be supplied from this network. In such a case, it can be a means of an image input device.
[0031]
In addition, a keyboard 15a and a mouse 15b as a pointing device are connected for operating the computer main body 12, and a speaker 18a and a microphone 18b are provided for multimedia support.
Furthermore, a display 17a and a color printer 17b are provided as image output devices. The display 17a has a display area of 800 pixels in the horizontal direction and 600 pixels in the vertical direction, and the above-described display of 16.7 million colors can be performed for each pixel. Of course, this resolution is only an example, and can be changed as appropriate, such as 640 × 480 pixels or 1024 × 768 pixels.
[0032]
A color printer 17b as a printing apparatus is an ink jet printer, and can print an image by adding dots on a printing paper as a recording medium using four color inks of CMYK. The image density is capable of high-density printing such as 360 × 360 dpi or 720 × 720 dpi, but the gradation table has a two-gradation expression such as whether or not color ink is applied. The color ink is not limited to such four colors, and it is possible to reduce the conspicuousness of dots by adding light cyan and light magenta, which are light in color, and not only the ink jet method but also color toner is used. It is also possible to employ an electrostatic photographic method.
[0033]
On the other hand, in order to display or output to the image output device while inputting an image using such an image input device, a predetermined program is executed in the computer main body 12. Among them, an operating system (OS) 12a is operating as a basic program, and the operating system 12a performs a print output to a display driver (DSP DRV) 12b for displaying on the display 17a and a color printer 17b. A printer driver (PRT DRV) 12c is installed. These types of drivers 12b and 12c depend on the models of the display 17a and the color printer 17b, and can be added to and changed from the operating system 12a according to the respective models. In addition, depending on the model, additional functions beyond standard processing can be realized. That is, various additional processes within an allowable range can be realized while maintaining a common processing system on the standard system called the operating system 12a.
[0034]
Of course, the computer main body 12 is provided with a CPU 12e, a RAM 12f, a ROM 12g, an I / O 12h, etc. as a premise for executing such a program, and the CPU 12e for executing arithmetic processing sets the RAM 12f in a temporary work area or setting. A basic program written in the ROM 12g is appropriately executed while being used as a storage area or a program area, and external devices and internal devices connected via the I / O 12h are controlled.
[0035]
The application 12d is executed on the operating system 12a as the basic program. The processing contents of the application 12d are various. The operation of the keyboard 15a and the mouse 15b as operation devices is monitored, and when operated, various external devices are appropriately controlled to execute corresponding arithmetic processing, Furthermore, the processing result is displayed on the display 17a or output to the color printer 17b.
[0036]
The computer system 10 can acquire image data by reading a photograph or the like with a scanner 11a as an image input device, and can also acquire image data captured with a digital still camera 11b or a video camera 11c. Image data as a moving image can be acquired. In addition, various image data captured in advance are often provided as CD-ROM software.
In recent years, it has become almost natural that such image data is in color, but there are many cases where the image data is intentionally made monotone in order to enjoy the expression. Conventionally, since the printing apparatus was only monochrome printing using only black ink, processing for monotone processing was performed as a matter of course. In many cases, such a colored monotone image is printed.
[0037]
In such a computer system 10, image data captured by the digital still camera 11b or the like can be captured by the computer main body 12, and can be printed by the color printer 17b through necessary image processing. In this case, a predetermined application 12d is started on the computer main body 12, and image data captured by the digital still camera 11b is directly captured as a print target, or image data already stored in an external storage device such as the hard disk 13b is captured. be able to. Accordingly, such processing constitutes the image acquisition means A1 shown in FIG.
[0038]
On the other hand, the application 12b can output the image data as it is to the printer driver 12c for printing, but the application 12b can also execute image processing. In the present invention, the luminance equivalent value of the image data (in this embodiment, the luminance in a strict sense is not handled, but the luminance equivalent value that is equivalent to the luminance is treated as the luminance) is statistically processed, and the image Understand the characteristics of At this time, if the image cannot be said to have good image quality by simply monotonizing the image as usual, a policy for correcting the luminance of the image data is determined based on the grasped characteristics. Accordingly, such processing constitutes the luminance distribution tabulating unit A2 and the luminance correspondence setting unit A3.
[0039]
Of course, when the policy for correction is determined in this way, the image data is corrected based on such criteria, and then output to the printer driver 12c for printing. Therefore, this modification process constitutes the image data conversion means A4.
That is, the image acquisition unit A1 shown in FIG. 1 realizes a process of acquiring image data having gradation value data for each element color. Based on this image data, the image acquisition unit A1 simply calculates the luminance equivalent value y and causes the luminance distribution tabulation unit A2 to tabulate. The luminance distribution tabulating means A2 tabulates the frequency distribution DB of luminance equivalent values so that the tendency of the luminance distribution can be known. Of course, it is also possible to realize aggregation other than the frequency distribution, but here the frequency distribution DB is selected from the viewpoint of simplicity of processing.
[0040]
The luminance correspondence setting means A3 sets the luminance correspondence so that an optimum image can be obtained when expressed in monotone based on the frequency distribution DB, but internally performs multistage processing. First, the luminance distribution width detecting means A31 obtains the maximum luminance Ymax and the minimum luminance Ymin of the distribution in the frequency distribution DB and the luminance distribution width Ydif based on these. Then, using these, the distribution width improvement LUT creation unit A32 generates a conversion table LUT1 indicating a correspondence relationship for improving the width of the luminance distribution. On the other hand, the frequency distribution DB is also referred to by the brightness determination means A33, and the median value Ymed of the distribution is obtained as a representative value representing the brightness of the image, and the brightness improvement LUT creation means A34 shows a correspondence relationship for improving the brightness of the image. A conversion table LUT2 is generated.
[0041]
The distribution width improvement LUT creation means A32 and the light / darkness improvement LUT creation means A34 each generate a correspondence that improves the luminance distribution from an individual viewpoint. Of course, each improvement can be made individually, but since the improvement using the conversion table can be easily integrated, the LUT integration means A35 generates an integrated conversion table LUT3 in which these are integrated.
The LUT 3 can improve the luminance equivalent value y to the last, but in the monotone conversion, a color like a sepia tone is preferred, and even if it is black and white, it must be expressed by the gradation value of the element color. There is no change in not becoming. Therefore, each color component LUT creation means A36 generates conversion tables LUT4R, LUT4G, and LUT4B that are directly converted from the luminance equivalent value y to the gradation value of each element color.
[0042]
The image data conversion means A4 obtains the luminance equivalent value y based on the original image data RGB, or refers to the LUT4R, LUT4G, and LUT4B based on the luminance equivalent value y generated by the image acquisition means A1, and obtains the reference result. Output as converted image data R ′, G ′, B ′. Of course, the LUT4R, LUT4G, and LUT4B include coloring elements as well as improvement of two luminance distributions of contrast and brightness, and a result obtained by collectively converting these can be obtained.
[0043]
In the following, a specific process in which the computer system 10 implements these mainly using software will be described in more detail. Such software is stored in the hard disk 13b and is read and operated by the computer main body 12. At the time of introduction, it is recorded on a medium such as the CD-ROM 13c-1 or the floppy disk 13a-1 and installed. Therefore, these media constitute a medium on which a monotone conversion program is recorded. Needless to say, these time-series processes constitute a monotone conversion method.
[0044]
In the present embodiment, the monotone conversion apparatus is realized as the computer system 10, but such a computer system is not necessarily required, and any system that handles image data and generates a monotone image may be used. For example, as shown in FIG. 3, the digital still camera 11b1 has a function of generating a monotone image, and is also applied to a configuration in which a monotone image is displayed on the display 17a1 or printed by the printer 17b1. Is possible.
[0045]
Further, as shown in FIG. 4, a printer 17b2 is connected without using a computer system, and color image data input through the scanner 11a2, the digital still camera 11b2, the modem 14a2, or the like is printed in monotone and printed. You can also In recent years, such a printer 17b2 is often used as a video printer for making a hard copy of a scene by connecting to a home television or video. In this case, it is possible to apply the present invention while adopting a function of making a monotone in a sepia tone instead of printing in color.
[0046]
FIG. 5 shows the control contents of the main image processing software in the monotone conversion apparatus in blocks.
In step 110, image data is input. The image data is read via the operating system 12a and stored in a predetermined work area. The image data itself is a single file. As shown in FIG. 6, the head portion is provided with profile data such as the size of the image and the number of colors, and thereafter, 3 pixels are expressed to represent each pixel in RGB 256 gradations. Byte areas are reserved for the number of pixels. Note that the image data may be read from the image input device, or an image data file already stored in the hard disk 13b or the like may be read.
[0047]
When the image data is read into the work area, the target pixel is moved in steps 120 to 140 as shown in FIG. Although the contents of the tabulation process are various, in this embodiment, the tabulation process is performed to obtain the feature amounts of “contrast” and “lightness”. After completing the aggregation process for all pixels, in step 150, an improvement method for optimizing the luminance distribution is set while analyzing the feature amount based on the aggregation result. In the following, description will be made focusing on these tabulations. FIG. 8 shows a flowchart for setting the luminance correspondence by analyzing the feature amount.
[0048]
The contrast indicates the width of the brightness of the entire image, and when it is felt that the contrast is not appropriate, there is mainly a desire to increase the width of the contrast. FIG. 9A shows a solid line in which the distribution of luminance equivalent values in each pixel of an image is tabulated as a histogram. When the distribution shown by the solid line is taken, the difference between the brightness of the bright pixel and the brightness of the dark pixel is small, but if the brightness distribution is widened as shown by the dashed line, the difference between the brightness of the bright pixel and the brightness of the dark pixel is large. As a result, the range of contrast is widened. Here, FIG. 9B shows luminance conversion for enlarging the contrast. Between the luminance y after conversion and the luminance Y after conversion,
Y = ay + b
If the conversion is performed based on the relationship, the difference between the pixels of the maximum luminance Ymax and the minimum luminance Ymin of the conversion source becomes large after conversion when a> 1, and the luminance distribution is widened as shown in FIG. become. Therefore, in order to create such a histogram, it is necessary to tabulate the interval from the maximum luminance value to the minimum luminance value as the contrast width. However, in this case, it is only luminance conversion, and if the image data has luminance as an element, it can be directly counted, but as described above, the image data is expressed in RGB 256 gradations. It does not have a luminance value directly. In order to obtain the luminance, it is necessary to perform color conversion to the Luv color space. However, since this is not a solution because of problems such as the amount of computation, conversion of the following equation that directly obtains the luminance from RGB used in the case of a television or the like Use an expression.
y = 0.30R + 0.59G + 0.11B
In addition, since it is not necessary to determine the brightness exactly like this,
y = (R + G + B) / 3
Furthermore, it is also possible to set only the G component as an approximate value from the difference in the weight of each component,
y = G
It is good. Of course, the luminance roughly calculated in this way is an actual luminance equivalent value, and if a simplified calculation is used, the calculation processing load is reduced and the speed can be increased. In Step 120 to Step 140, 3 bytes as image data of each pixel is read while moving the target pixel, and the luminance y is calculated based on the same equation. In this case, the luminance y is also expressed by 256 gradations, and the frequency for the calculated luminance y is added one by one.
That is, in step 120, the pointer indicating the target pixel is set to the initial position in order to scan and process the image, and the pointer is moved in step 135 until it is determined in step 140 that all pixels have been completed. Repeat the loop process. Also, what is executed for each pixel is the calculation of the luminance equivalent value of the pixel of interest performed in step 125 and the update of the frequency distribution performed in step 130. While calculating the luminance equivalent value (Y) for all the pixels, the variable DB (Y) representing the number of pixels having the same luminance equivalent value is incremented by “1”. A frequency distribution (histogram) is obtained.
[0049]
Note that the conversion to black and white that does not need to be colored may use this luminance, and is realized by matching the RGB component values with the obtained gradation values of the luminance.
Steps 120 to 140 for obtaining the histogram of the luminance distribution in this way are the luminance distribution totaling process, and the luminance correspondence is set while analyzing the feature amount in the flowchart shown in FIG. 8 based on this histogram.
First, at step 210, both ends of the luminance distribution are obtained. The luminance distribution of the photographic image appears generally in a mountain shape as shown in FIG. Of course, there are various positions and shapes. The width of the luminance distribution is determined depending on where the both ends are determined, but a point where the base extends and the number of distributions becomes “0” cannot be the both ends. This is because the number of distributions may change around “0” in the base portion, and if it is statistically viewed, it changes while approaching “0” as much as possible.
[0050]
For this reason, in the distribution range, portions that are closer to the inside by a certain distribution ratio from the side with the highest luminance and the side with the lowest luminance are defined as both ends of the distribution. In the present embodiment, as shown in the figure, this distribution ratio is set to 0.5%. Of course, this ratio can be appropriately changed. In this way, by cutting the upper end and the lower end by a certain distribution ratio, it is possible to ignore white spots and black spots caused by noise or the like. In other words, if such a process is not performed, if there is even a single point of white or black, it will be at both ends of the luminance distribution. Although it is “0” and the uppermost end is gradation “255”, such a thing can be achieved by setting a portion that is inward by 0.5% of the number of pixels from the upper end portion as an end portion. Disappear. Then, 0.5% of the number of pixels is calculated based on the actually obtained histogram, and the number of distributions is accumulated inwardly starting from the luminance value at the upper end and the luminance value at the lower end in the reproducible luminance distribution. Then, the luminance value having a value of 0.5% becomes the maximum luminance Ymax and the minimum luminance Ymin.
[0051]
The width Ydif of the luminance distribution is the difference between the maximum luminance Ymax and the minimum luminance Ymin.
Ydif = Ymax−Ymin
It becomes.
On the other hand, the width Ydif of the luminance distribution is a feature amount analyzed based on the image data. In the process of step 215, an improvement parameter is derived in order to set a luminance correspondence relationship based on the feature amount. As the image processing for enlarging the contrast based on the width Ydif of the luminance distribution, the inclination a and the offset b may be determined according to the luminance distribution. For example,
a = 255 / (Ymax−Ymin)
b = −a · Ymin or 255−a · Ymax
If this is the case, the luminance distribution with a narrow width can be expanded to a reproducible range. However, when the luminance distribution is expanded by making the maximum use of the reproducible range, the highlight portion may be white and the high shadow portion may be black. In order to prevent this, it is only necessary to leave “5” as a luminance value as a range that does not expand to the upper end and the lower end of the reproducible range. As a result, the parameters of the conversion equation are as follows:
a = 245 / (Ymax−Ymin)
b = 5-a · Ymin or 250-a · Ymax
In this case, it is preferable not to perform conversion in the range of Y <Ymin and Y> Ymax.
[0052]
Moreover, it is not necessary to calculate every time in this conversion. If the luminance range takes values “0” to “255”, a conversion result is previously set for each luminance value, and a conversion table is formed as shown in FIG. This conversion table is substantially synonymous with the distribution width improvement tone curve, and the conversion table is formed in step 220. The conversion table created here is called LUT1.
[0053]
If a monochrome monotone image is simply obtained, the conversion result Y of this conversion table is used, and the image data (R0, G0, B0) before conversion is converted into image data (Y1, Y1, Y1) after conversion. That's fine.
That is, in step 150, the process of analyzing the feature amount corresponds to the process of obtaining the maximum brightness Ymax and the minimum brightness Ymin described above, and the work of setting the brightness correspondence relationship is obtained from the conversion formula while obtaining the width Ydif of the brightness distribution from these. This corresponds to processing for obtaining the parameters a and b and creating a conversion table. If this is the only correspondence setting process, the image data conversion process in step 160 designates such a conversion table and converts the image data after conversion from the image data before conversion (R0, G0, B0). (R1 (= Y1), G1 (= Y1), B1 (= Y1)) is generated.
[0054]
Further, the luminance distribution width detection process in step 210 corresponds to the luminance distribution width detection means A31 shown in FIG. 1, and the distribution width improvement parameter derivation process in step 215 and the distribution width improvement conversion table creation process in step 220 are shown in FIG. This corresponds to the distribution width improvement LUT creation means A32 shown.
Next, brightness will be described. The lightness as the feature amount of the image here means an index of lightness and darkness of the entire image, and the median value (median) Ymed of the distribution obtained from the above-described histogram is used. Accordingly, the aggregation process in this case is performed simultaneously with the aggregation process for contrast, as before.
[0055]
On the other hand, when analyzing a feature value, a difference (Ymed_target−Ymed) from Ymed_target, which is an ideal value of lightness, may be calculated. The actual value of the ideal value Ymed_target uses “106”, but is not fixed. Further, it may be changed to reflect the preference. Of course, the process for calculating the difference (Ymed_target−Ymed) from the ideal value of Ymed_target in this way corresponds to the brightness / darkness detection process in step 225.
[0056]
In the case where the luminance correspondence relationship for brightness is set using this feature quantity (Ymed_target-Ymed), the following is performed. Whether the image is bright or not can be evaluated based on whether the median value Ymed is larger or smaller than the ideal value Ymed_target. For example, if the median value Ymed is “85”, it is smaller than the ideal value Ymed_target “106”. Therefore, the median value Ymed is first evaluated as “dark”, and secondarily the degree of darkness is It is expressed numerically as “106-85”.
[0057]
FIG. 11 (a) shows a luminance histogram. When the peaks of the luminance distribution are close to the dark side as shown by the solid line, the peaks are shown on the bright side as shown by the wavy line. On the contrary, when the peak of the luminance distribution is on the whole bright side as shown by the solid line in FIG. 11B, the peak is on the whole dark side as shown by the wavy line. It is good to move. In such a case, instead of performing linear luminance conversion as shown in FIG. 9B, luminance conversion using a so-called γ curve as shown in FIG. 11C may be performed.
[0058]
It is necessary to move the peaks of the luminance distribution in this way, which corresponds to the case where the brightness of the image is not within the appropriate range, and the peaks of the same luminance distribution are moved to obtain an appropriate distribution as a whole. The correspondence will be derived.
In the correction using the γ curve, the entire image becomes bright when γ <1, and the entire image becomes dark when γ> 1. In the above example, if the median value Ymed increases by “21”, it will coincide with the ideal value Ymed_target. However, it is not easy to accurately increase “21” using the γ curve. For this reason, as shown in FIG. 12, the value of γ corresponding to every increment of “5” may be set for the evaluation value (Ymed_target−Ymed). In this example, the value of γ is varied by “0.05” corresponding to the variation amount “5” of the evaluation value, but it goes without saying that the correspondence between the two can be changed as appropriate.
[0059]
It is also possible to automatically set the value of γ as in the case of contrast correction. For example,
γ = Ymed / 106
Or
γ = (Ymed / 106) ** (1/2)
The value of γ may be obtained as Of course, the conversion table as shown in FIG. 11B is also formed for the luminance conversion by the γ curve. Here, the process for obtaining γ from the table shown in FIG. 12 based on the evaluation value and the process for obtaining γ using the above-described calculation formula correspond to the brightness improvement parameter derivation process in step 230, and further the brightness improvement in step 235. The conversion table creation processing corresponds to processing for creating a conversion table in which conversion values are obtained in advance in the range of luminance “0” to “255” using the γ. Note that the conversion table finally created by this light / dark improvement conversion table creation processing is called LUT2.
[0060]
That is, the work for analyzing the feature amount corresponds to the work for obtaining the median value Ymed or the evaluation value (Ymed_target-Ymed), and the process for creating the conversion table while obtaining the γ correction value from the brightness correspondence setting process. Applicable. If this is the only luminance correspondence, in the image data conversion process in step 160, such a conversion table is designated, and the image data (R1, G0, B0) after conversion from the image data (R0, G0, B0) of each pixel is converted. G1, B1) is generated.
[0061]
The brightness detection process in step 225 corresponds to the brightness determination means A33 shown in FIG. 1, and the brightness improvement parameter derivation process in step 230 and the brightness improvement conversion table creation process in step 235 are the brightness improvement LUT creation means shown in FIG. Corresponds to A34.
By the way, in the present embodiment, two conversion tables are created as described above. In actual image data conversion, it is wasteful to convert sequentially using two conversion tables. For this reason, in step 240, processing for integrating the two conversion tables is performed. A detailed flowchart for the LUT integration processing is shown in FIG. Each of the two conversion tables LUT1 and LUT2 described above has a gradation range of “0” to “255”. For this reason, the conversion value of the conversion table LUT3 may be obtained by integrating the values converted by the LUT2 after the conversion by the LUT1 over the entire gradation range. First, the pointer variable i is cleared to “0” in step 310, and a loop of i = 0 to 255 is executed by the increment process in step 330 and the loop end determination process in step 335.
[0062]
In the loop, first, in step 315, the converted value of LUT1 for the gradation value i is stored in the variable i1, and in step 320, the converted value of LUT2 for the converted value i1 is stored in the variable i2. Since this conversion value i2 is a result of referring to two conversion tables, in step 325, it is set as a conversion value for the gradation value i in the new conversion table LUT3. FIG. 14 shows a process of integrating the conversion tables LUT1 and LUT2. In this way, it is possible to easily create a conversion table corresponding to the execution of all the luminance correspondences, regardless of the number of luminance correspondence relationships. Of course, such LUT integration processing corresponds to the LUT integration means A35 shown in FIG.
[0063]
In this case, since the individual conversion tables LUT1, LUT2 only represent intermediate values, it is not necessary to match the gradation range to the original gradation range, and a more detailed gradation range can be set. . For example, if 768 gradations are set in the intermediate stage and 256 gradations are set in the integrated conversion table, it is possible to prevent the error from gradually increasing during a plurality of conversion tables. it can.
[0064]
In setting the luminance correspondence, the γ curve is used in the case shown in FIG. 11C, and the straight line having a constant slope a and offset b is used in the case shown in FIG. 9B. These can be said to be included in a broadly defined tone curve in the sense that the correspondence relationship of gradation values can be determined in a wide range using one or two parameters.
A monotone image is not necessarily black and white, and a colored monotone image is also preferred. For this reason, when the LUTs are integrated, the color component LUT creation process is executed in step 245. FIG. 15 is a detailed flowchart thereof.
[0065]
Generally, when a representative monotone color (a set of RGB with the highest saturation) is (Rs, Gs, Bs), the corresponding luminance value is ys, and the converted luminance value is Y1. The converted RGB values (R1, G1, B1) are
R1 = Y1 * Rs / ys
G1 = Y1 * Gs / ys
B1 = Y1 * Bs / ys
It can be. FIG. 16A is a graph showing the relationship in which the component ratio of the colored monotone is constant. In this graph, the horizontal axis represents the luminance value y of the conversion source, and the vertical axis represents the gradation value of each color after conversion (which can be said to be the luminance value of each color). As described above, with respect to the luminance value when the saturation is highest, the RGB combination is (Rs, Gs, Bs) with respect to ys, and the ratio of the RGB gradation values at this time is the luminance. It remains constant regardless of the value y.
[0066]
According to the above calculation formula, the G component is also calculated. However, considering the degree of influence of the G component on the luminance, the luminance value ys is substituted as it is as the G component, and the luminance for the R component and the B component is determined. It may be calculated from the luminance value ys using the differences Δ1, Δ2 from the G component when the value is ys. That is,
R1 = Y1 * (1 + Δ1 * (Y1 / ys))
G1 = ys
B1 = Y1 * (1−Δ2 * (Y1 / ys))
Of course, since the conversion table LUT3 has already been created, the RGB values (R1, G1, B1) when Y1 is changed over the entire gradation range may be prepared as the conversion table values.
[0067]
In this example, the component ratio (R: G: B) of each element color is always constant, but for example, the component (R1) of each element color in the luminance value (ys) where this color appears most frequently. , G1, B1) coincides with the above-described composition ratio (R: G: B) (Δ1 = RG, Δ2 = GB), and the other regions become darker or brighter. The components can be made to gradually match. This correspondence is shown in FIG.
[0068]
This graph shows a conversion mode using the above-described γ curve. That is, a γ value is calculated such that a set of RGB in the luminance value ys is (Rs, Gs, Bs), and the RGB value when Y1 is changed over the entire gradation range using the γ value ( R1, G1, B1) is obtained and used as the conversion table value. In the case of this graph, since there is a relationship of Rs> Gs> Bs, at least Rs> Y1, and Y1> Bs. Therefore, the R component is a downward convex curve with γ <1, and the B component is an upward convex curve with γ> 1. Strictly speaking, γ can be 1 or more and less than 1 for the G component, but in the graph, it is simplified and expressed as γ = 1. However, in this case, as described above, it is also possible to prepare tone curves for conversion only for the R component and the B component with the G component as a reference.
[0069]
Of course, when the luminance value is low and the luminance value is high, the above-described composition ratio (R: G: B) does not match. However, when the luminance value reaches the maximum value, the above composition ratio cannot be maintained, and when the luminance value is low and when the luminance value is high, it is actually black or white. Thus, the change mode that converges to the luminance value ys is natural.
In the luminance correspondence setting process, the coloring LUT integration process is performed in step 245 regardless of whether or not coloring is performed. As shown in FIG. 15, the coloring instruction parameter CL is acquired in the first step 410 of the coloring LUT integration processing. The coloring instruction parameter CL may be substituted with a value representing a color in advance, and the value may be read in step 410, or the operator is prompted to input on the display 17a1, and the keyboard 15a and mouse 15b are operated. You may make it set the value according to. Of course, the color to be colored and the parameter are associated with each other in advance, and each color component when the parameter is specified has a two-dimensional table structure.
LUT_R (CL, 0-255)
LUT_G (CL, 0-255)
LUT_B (CL, 0-255)
Set a value in the conversion table. Since there are cases where black and white monotone is used without color, a conversion table in which each color component is matched for each gradation is prepared. For example, when the coloring instruction parameter CL is “0”, this conversion table is prepared. To use. Of course, this coloring LUT integration process corresponds to each color component LUT creating means shown in FIG.
[0070]
Next, in step 415, the variable i of the pointer is cleared to “0”, and the loop of i = 0 to 255 is executed by the increment process of step 435 and the loop end determination process of step 440. Within the loop, in steps 420 to 430, each color component in the gradation value of the variable i is set by the following equation.
LUT4R (i) = LUT_R (CL, LUT3 (i))
LUT4G (i) = LUT_G (CL, LUT3 (i))
LUT4B (i) = LUT_B (CL, LUT3 (i))
In this example, a conversion table representing the conversion result over the entire gradation range is prepared for each color. However, a γ correction value for correcting each color is prepared for each coloring instruction parameter, and the value of the conversion table LUT3 is used. Then, the calculation for γ correction may be executed to obtain the values of LUT4R, LUT4G, and LUT4B.
[0071]
FIG. 17 shows a process of integrating the conversion tables LUT_R, LUT_G, and LUT_B for coloring with the conversion table of LUT3.
The conversion table of LUT3 shown in FIG. 17 is realized as a correspondence relationship that realizes contrast correction and brightness correction in one step as described above. That is, a luminance equivalent value Y obtained by correcting the luminance distribution based on the actual luminance equivalent value y of the target pixel is obtained.
[0072]
On the other hand, LUT_R, LUT_G, and LUT_B are conversion tables for expressing a predetermined monotone instructed by the coloring instruction parameter CL. If a single luminance equivalent value Y1 is input, each element color at the luminance equivalent value is input. RGB gradation values are obtained. Of course, by referring to the LUT 3 with the luminance equivalent value y before correction and referring to the LUT_R, LUT_G, and LUT_B with the referenced luminance equivalent value Y1, the optimum luminance distribution can be corrected with respect to the luminance equivalent value y before correction. In this way, RGB gradation values colored to a desired color are obtained. LUT4R, LUT4G, and LUT4B shown in the figure are obtained by integrating conversion tables so that this can be realized by one conversion.
[0073]
When the analysis of the feature amount and the setting of the luminance correspondence are completed as described above, the image data conversion process is executed in step 160. FIG. 18 shows a more detailed flowchart of the image data conversion process.
In the conversion of the image data, the image data of each pixel is corrected while moving the target pixel as shown in FIG. The position of the target pixel is indicated by a pointer. In step 510, the pointer is moved to the initial position. In step 515, the luminance equivalent value y of the target pixel is calculated in the same manner as described above, and in steps 520 to 530, the conversion table LUT4 is referred to with the luminance equivalent value y, and each color component R ′, G ′, B ′ is calculated. Ask for. The conversion itself is now complete, and the corrected image data is output in step 535. Thereafter, in step 540, the pointer is moved to the next pixel. At this time, if it is determined in step 545 that all pixels have been completed, the image data conversion process is terminated, and it is determined that all pixels have not been completed. For example, the processing from step 515 onward is repeated.
[0074]
In this embodiment, the luminance equivalent value is calculated twice at the time of the luminance distribution aggregation processing and at the time of image data conversion. However, as shown by the wavy line in FIG. Is output and the brightness distribution is aggregated and stored in the work area, the image data conversion process can read the brightness equivalent value of each pixel from this work area and execute the process. You do n’t have to. Further, when saving as a luminance equivalent value in this way, there is one element per pixel. For this reason, 1 byte of 1/3 is sufficient as compared with the case of using a total of 3 bytes for each RGB component. Therefore, the file capacity is 1/3 that of the original image data.
[0075]
Next, the operation of the present embodiment configured as described above will be described.
Assuming that the image data captured by the digital still camera 11b is to be printed in sepia, the user launches an application 12d such as image printing software on the computer system 10 and uses a cable connection or removable media. Image data is taken in from the digital still camera 11b. Then, “Sepia” is selected as the image processing from the operation menu of the application 12d, and “Print” processing is selected. The outline of this process is executed according to the flowchart shown in FIG. In this case, since the image data has already been captured, it is assumed that the input processing in step 110 has been executed, and the processing in steps 120 to 140 is executed. That is, the luminance equivalent value for each pixel is obtained, and the luminance distribution is totaled over all pixels. It should be noted that the summation result need not be strict, and may be summed up for the thinned out pixels rather than over all the pixels.
[0076]
Here, description will be made with reference to specific subjects and photographs. Assume that the subject is a ball shown in FIG. This ball has a belt-like color-coded pattern. If you compare it to the earth, it is assumed that the ball is lighter on the north and south poles and darker on the equator. When the digital still camera 11b photographed as a color image, it became as shown in FIG.19 (b). Although the photograph itself is an image with a narrow contrast, since it is a color image, the band-like color-coded pattern can be recognized from the difference in color. In the drawing, the band is shown in the sense that the color classification is understood, although it does not correspond to the color density. If an image with such a low contrast is converted into a monotone as it is, a band-like pattern that can barely be identified as shown in FIG.
[0077]
However, in the feature amount analysis brightness correspondence setting process executed as step 150, the conversion table LUT3 for deriving the contrast width Ydif or the median value Ymed of the image data from the brightness distribution and improving this is obtained. Form. In addition, since the conversion table LUT4 for coloring a sepia tone monotone is formed while taking advantage of the correspondence relationship for improving the luminance distribution, if the image data is modified based on the conversion table LUT4, the contrast width is improved. However, the brightness is also well distributed. Of course, as a result, the entire image becomes a sepia-tone monotone image, and the band pattern can be recognized as it is as a monotone image as shown in FIG. That is, multi-stage processing with completely different properties such as monochrome image correction and coloring in a certain color is performed by batch conversion, and the result is very good image quality as a monotone image.
[0078]
In this way, when color image data is input and monotonized, the luminance distribution in the image data is tabulated (steps 120 to 140), and the luminance correspondence is set using the tabulation result (step 150). Since the image data is modified based on the luminance correspondence and converted to a monotone image, the image quality can be improved as compared to the case where the monotone image is simply converted based on the luminance alone. It is possible to perform a multi-stage conversion of improving the luminance distribution and coloring process all at once.
[Brief description of the drawings]
FIG. 1 is a schematic configuration diagram corresponding to a claim of a monotone conversion device according to an embodiment of the present invention;
FIG. 2 is a block diagram of hardware embodying the monotone conversion device.
FIG. 3 is a schematic block diagram showing another application example of the monotone conversion device of the present invention.
FIG. 4 is a schematic block diagram showing another application example of the monotone conversion device of the present invention.
FIG. 5 is a main flowchart in the monotone conversion apparatus of the present invention.
FIG. 6 is a diagram illustrating a configuration of an image data file.
FIG. 7 is a diagram illustrating a state in which a processing target pixel is moved.
FIG. 8 is a flowchart of feature amount analysis brightness correspondence setting processing;
FIG. 9 is a diagram showing a luminance distribution (a) and a conversion relationship (b) when the luminance distribution needs to be enlarged.
FIG. 10 is a diagram showing a luminance distribution end processing (a) and a conversion table (b) when the luminance distribution is enlarged;
FIG. 11 is a diagram illustrating a concept (a) for brightening, a concept (b) for darkening, and a method (c) by γ correction.
FIG. 12 is a diagram illustrating a correspondence relationship between an evaluation value of brightness and γ.
FIG. 13 is a flowchart of LUT integration processing.
FIG. 14 is a diagram showing an LUT integration process;
FIG. 15 is a flowchart of a coloring LUT integration process.
FIG. 16 is a diagram showing a correspondence relationship (a) for determining a component so that the ratio of each component is constant for coloring in monotone, and a configuration in which the ratio of each component is constant at an optimum gradation value. It is a graph which shows the correspondence (b) which determines a minute.
FIG. 17 is a diagram illustrating a process of integrating coloring LUTs.
FIG. 18 is a flowchart of image data conversion processing.
FIG. 19 is a diagram showing a ball (a) of a subject and a color image (b) thereof.
FIG. 20 is a diagram of an image (a) when normal monotoning is performed and an image (b) when monotoning of the present invention is performed.
[Explanation of symbols]
10. Computer system
11a ... Scanner
11a2 ... Scanner
11b ... Digital still camera
11b1 ... Digital still camera
11b2 ... Digital still camera
11c ... Video camera
12 ... Computer body
12a ... Operating system
12b ... Display driver
12b ... Driver
12c: Printer driver
12d Application
13a ... floppy disk drive
13b ... Hard disk
13c ... CD-ROM drive
14a ... modem
14a2 Modem
15a ... Keyboard
15b ... Mouse
17a ... Display
17a1 ... Display
17b ... Color printer
17b1 Color printer
17b2 ... Color printer
18a ... Color facsimile machine
18b ... color copying machine

Claims (7)

Image acquisition means for expressing the image as each pixel in a dot matrix and acquiring image data expressed in gradation for each pixel with a predetermined element color obtained by color separation;
A luminance distribution summary means for aggregation of luminance equivalent value of each pixel based on the image data,
A luminance conversion table for changing the luminance distribution by converting the luminance equivalent value is derived on the basis of the aggregated luminance distribution, and the luminance equivalent value is converted into an element color expressing a monotone having a predetermined tone. A table setting unit that sets a conversion table for each element color and generates an integrated conversion table for each element color by integrating the luminance conversion table with each conversion table for each element color;
By inputting the luminance equivalent value of each pixel in the image data to each integrated conversion table for each element color, and obtaining the gradation value for each element color of each pixel as a conversion result by each integrated conversion table, the predetermined color tone A monotone conversion apparatus comprising: image data conversion means for acquiring monotone image data of the above. In the monotone conversion device according to claim 1,
  Means for obtaining a coloring instruction for instructing a monotone color tone in response to an external input;
  The table setting means integrates the luminance conversion table into a conversion table for each element color that defines the conversion relationship between the luminance equivalent value and the element color representing the monotone of the color indicated by the acquired coloring instruction. Characteristic monotone conversion device. In monotone conversion apparatus according to claim 1 or claim 2, the table setting means converts the composition ratio of each element colors of the elements each color to percentage for representing monotone of the predetermined tone A monotone conversion apparatus using a tone curve that smoothly changes a conversion result over all gradation values while realizing a constant composition ratio with a certain luminance equivalent value as a table . 4. The monotone conversion device according to claim 1, wherein the table setting unit sets the contrast range while setting a range from the maximum luminance to the minimum luminance derived based on the luminance distribution as a contrast width. A monotone conversion device for deriving a luminance conversion table for converting from original luminance to modified luminance so that the width of the image becomes an appropriate width. 5. The monotone conversion device according to claim 1, wherein the table setting means has the same luminance distribution as a whole when the brightness of an image derived based on the luminance distribution is not within an appropriate range. A monotone conversion device for deriving a luminance conversion table for converting from original luminance to modified luminance so as to obtain an appropriate distribution. A monotone conversion method for representing an image as a pixel in a dot matrix and obtaining image data expressed in gradation for each pixel with a predetermined element color obtained by color separation, and generating and outputting monotone image data,
A step of tabulating the luminance equivalent value of each pixel based on the image data;
A luminance conversion table for changing the luminance distribution by converting the luminance equivalent value is derived on the basis of the aggregated luminance distribution, and the luminance equivalent value is converted into an element color expressing a monotone having a predetermined tone. Setting a conversion table for each element color, and generating an integrated conversion table for each element color by integrating the luminance conversion table into each conversion table for each element color; and
By inputting the luminance equivalent value of each pixel in the image data to each integrated conversion table for each element color, and obtaining the gradation value for each element color of each pixel as a conversion result by each integrated conversion table, the predetermined color tone monotone conversion method characterized by comprising the step of obtaining a monotone image data. The images acquired image data gradation representation for each pixel in a predetermined element color that color separation with expressed as each pixel of the dot matrix, a monotone conversion program for executing processing for generating a monotone image data to the computer A recording medium,
A function of counting the luminance equivalent values of each pixel based on the image data;
A luminance conversion table for changing the luminance distribution by converting the luminance equivalent value is derived on the basis of the aggregated luminance distribution, and the luminance equivalent value is converted into an element color expressing a monotone having a predetermined tone. A function for generating an integrated conversion table for each element color by setting a conversion table for each element color and integrating the luminance conversion table into each conversion table for each element color;
By inputting the luminance equivalent value of each pixel in the image data to each integrated conversion table for each element color, and obtaining the gradation value for each element color of each pixel as a conversion result by each integrated conversion table, the predetermined color tone A medium having a monotone conversion program recorded thereon, which causes the computer to execute a function of acquiring the monotone image data.

Images