JP2001222711A - Image processing method and image processor - Google Patents

Image processing method and image processor

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Publication number
JP2001222711A
JP2001222711A JP2000032256A JP2000032256A JP2001222711A JP 2001222711 A JP2001222711 A JP 2001222711A JP 2000032256 A JP2000032256 A JP 2000032256A JP 2000032256 A JP2000032256 A JP 2000032256A JP 2001222711 A JP2001222711 A JP 2001222711A
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Japan
Prior art keywords
color
distribution
lo
reg
image processing
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Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
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JP2000032256A
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Japanese (ja)
Inventor
Hiroshi Mori
浩 森
Original Assignee
Canon Inc
キヤノン株式会社
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Priority to JP2000032256A priority Critical patent/JP2001222711A/en
Publication of JP2001222711A publication Critical patent/JP2001222711A/en
Withdrawn legal-status Critical Current

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Abstract

PROBLEM TO BE SOLVED: To provide an image processing method and an image processor which can perform contrast correction corresponding to a color bias in the case of processing a multi-level image of a plurality of colors. SOLUTION: The features of an image luminance frequency distribution for every color are compared to judge, whether or not a color bias exists (S204). When the existence of color bias is judged in the judgement process, contrast correction is performed on the basis of the mutual relation of the luminance frequency distributions of respective colors (S206).

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

[0001] 1. Field of the Invention [0002] The present invention relates to an image processing method and apparatus, and more particularly, to an image processing method and apparatus relating to contrast correction of image data.

[0002]

2. Description of the Related Art Conventionally, in contrast correction processing, a white point and a black point have been determined for an image having low contrast, and image processing has been performed so that the gradation between them is the maximum gradation difference.

For example, conventionally, a contrast correction process has been performed according to a flowchart shown in FIG.

In step S501, a multi-valued image to be subjected to contrast correction is input to a memory. The multi-valued image is a color image having a luminance gradation of 8 bits for each of RGB read by an image input device such as a scanner.

In S502, a luminance histogram of the multi-valued image input in S501 is calculated. In the luminance histogram, the numerical frequency of the luminance gradation of all pixels of the image is obtained for each of RGB.

In S503, the lo point and the hi point are searched from the luminance histogram calculated in S502.
The lo point is a luminance value from black (numerical value 0) to 1% of all pixels, and the hi point is a luminance value from white (numerical value 255) to 1% of all pixels. These are obtained for each of RGB, and R_lo, R_hi, G_lo, G_h are respectively obtained.
Represented by i, B_lo, B_hi.

In S504, a contrast correction table is created from the numerical values of the lo point and the hi point calculated in S503. The contrast correction table maps the luminance values for each of the RGB such that the lo point is black (numerical value 0) and the hi point is white (numerical value 255). FIG. 5 shows an example of the contrast correction table.

In step S505, the contrast of the multivalued image is corrected using the contrast correction table created in step S504.

[0009]

However, in the above-described conventional contrast correction processing, there is a problem that the color balance is lost in an image in which the constituent colors are biased. For example, if contrast correction is performed on an image of a sunset sky, the entire image will be reddish and there will be no white areas in the screen. Problems occur.

Further, when a document having a wide dynamic range of the exposure amount such as a negative film and having a non-linear characteristic is read as image data, the distribution of image information in the density range of the film is not improved due to the image exposure condition. Be equal.
Therefore, when a negative film is captured by a scanner, it is difficult to perform appropriate contrast correction.

SUMMARY OF THE INVENTION The present invention has been made to solve the problems existing in the above prior art, and an object of the present invention is to provide an image processing method and apparatus capable of performing contrast correction corresponding to color bias. To provide.

[0012]

In order to achieve the above object, a method according to the present invention is an image processing method for processing a multi-tone image of a plurality of colors, characterized by the characteristic of the luminance frequency distribution of the image for each color. Comparing, and determining whether there is color bias, and, when the determination step determines that there is color bias, performs contrast correction based on the correlation of the luminance frequency distribution of each color. Correction step to be performed.

The determining step includes a step of generating a luminance frequency distribution from image data; a step of determining a distribution width of the luminance frequency distribution for each color; and a step of determining a distribution width ratio of each color from the distribution width. A target ratio deriving step of obtaining a distribution width target ratio of each color from the characteristics of the luminance frequency distribution, and a step of determining that there is a color bias when the distribution width ratio deviates from the distribution width target ratio by a predetermined value or more. , Is included.

The target ratio deriving step may include any one of a lower limit luminance value, an upper limit luminance value, an average luminance value, or an intermediate value between the lower limit luminance value and the upper limit luminance value in the luminance frequency distribution;
Alternatively, the method further includes a step of obtaining the distribution width target ratio according to the combination.

The correcting step includes a step of changing the maximum gradation width of another color based on the maximum gradation width of any one color.

The correcting step includes a step of changing an upper limit value and / or a lower limit value of a maximum gradation width of each color to make a distribution width ratio of each color equal to the distribution width target ratio.

In order to achieve the above object, an apparatus according to the present invention is an image processing apparatus for processing a multi-tone image of a plurality of colors. Determining means for determining whether or not there is a bias; and correcting means for performing contrast correction based on the correlation of the luminance frequency distribution of each color when the determining means determines that there is a color bias. It is characterized by having.

A determination means for generating a luminance frequency distribution from the image data; a distribution width deriving means for determining a distribution width of the luminance frequency distribution for each color; and a distribution width ratio of each color from the distribution width. Distribution width ratio deriving means, target ratio deriving means for obtaining a distribution width target ratio for each color from the characteristics of the luminance frequency distribution, and when the distribution width ratio deviates from the distribution width target ratio by a predetermined value or more, Determining means for determining that there is a bias.

The target ratio deriving means may select one of a lower limit luminance value, an upper limit luminance value, an average luminance value, or an intermediate value between the lower limit luminance value and the upper limit luminance value in the luminance frequency distribution,
Alternatively, it is characterized by including means for obtaining the distribution width target ratio according to the combination.

The correction means includes means for changing the maximum gradation width of another color based on the maximum gradation width of any one color.

The correction means includes means for changing the upper limit value and / or the lower limit value of the maximum gradation width of each color to make the distribution width ratio of each color equal to the distribution width target ratio.

In order to achieve the above object, a storage medium according to the present invention is a computer-readable memory storing an image processing program for processing a multi-tone image of a plurality of colors, wherein the image processing program is provided for each color. The code of the determining step of comparing the characteristics of the luminance frequency distribution of the image and determining whether or not there is a color bias, and the luminance frequency distribution of each color when the determining step determines that there is a color bias. And a code for a correction step for performing contrast correction based on the mutual relationship.

[0023]

Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings. However, the relative arrangement of components described in this embodiment, formulas, numerical values, etc., unless otherwise specified,
It is not intended to limit the scope of the present invention only to them.

(Embodiment) First, a contrast correction process according to an embodiment of the present invention will be described with reference to the flowchart of FIG.

In step S201, a multi-valued image to be subjected to contrast correction is input to a memory. The multi-valued image is a color image having a luminance gradation of 8 bits for each of RGB read by an image input device such as a scanner.

In S202, a luminance histogram of the multi-valued image input in S201 is calculated. In the luminance histogram, the numerical frequency of the luminance gradation of all pixels of the image is obtained for each of RGB.

In S203, the lo point and the hi point are searched from the luminance histogram calculated in S202.
The lo point is a brightness value (lower limit of the histogram) from black (numerical value 0) to 1% of all pixels, and the hi point is a brightness value (upper limit value of histogram) from white (numerical value 255) to 1% of all pixels. is there. These are obtained for each of RGB, and R_lo, R_hi, G_lo, G_h are respectively obtained.
Represented by i, B_lo, B_hi.

In S204, it is determined from the numerical values of the lo point and the hi point calculated in S203 whether or not the original image is an image having a color bias.
The value of the hi point is updated so that the color balance is not lost. This part is the central part of the present embodiment. FIG. 3 shows an example of a histogram of a color-biased image,
An example of updating the lower limit value and the upper limit value of G and B when R is set as a reference (the reference is set because the distribution width of R is the maximum) is shown.

In S205, the value calculated in S203 or
A contrast correction table is created from the numerical values of the lo point and the hi point updated in 204. The contrast correction table maps the luminance values for each of the RGB such that the lo point is black (numerical value 0) and the hi point is white (numerical value 255). FIG. 4 shows an example of the contrast correction table.

In step S206, the contrast of the multivalued image is corrected using the contrast correction table created in step S205.

Next, image processing that best represents the features of the present invention, which is also S204 in FIG. 2, will be described in more detail with reference to FIGS.

FIGS. 1A to 1D are flowcharts showing the flow of image processing for determining color deviation and correcting gradation width in the present embodiment.

In S101, the distribution width lower limit range_l
Determine the limit. The lower limit of the distribution width is determined for each of RGB using the table of FIG. 5 according to the value of lo_min.

In step S102, the distribution width target ratio t for each color is calculated from the distribution width lower limit range_limit determined in step S101.
"art_rate" and the distribution width R-range of RGB
The distribution width ratio range_rate of each color is obtained from e, G_range, and B_range.

In S103, it is determined whether or not the image has a color bias. Target distribution width ratio tar obtained in S102
If the difference between “get_rate” and the distribution width ratio “range_rate” is more than a predetermined value (here, 3%) for any of the RGB colors, it is determined that there is a color bias, and S104 is performed.
Otherwise, the process proceeds to end and the process ends.

In S104, R_range = range
If _max, the flow shifts to step S105 to perform contrast correction based on R, and if not, shifts to step S118. The range_max is the largest value among the ranges of RGB.

In S105, R which is range_max
The distribution width ratio of G and B to _range is target
The target distribution width for obtaining the same value as t_rate is calculated by the following equation.

Set_range_G = (range_max * range_limit_G) / range_limit_R ... (1) set_range_B = (range_max_range_limit_B in the case where the distribution of the target_Range_Reg_Reg_Reg_Reg_Reg_Reg_Right_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Right_Reg_Reg_Right_Reg_Reg_Right_Reg_Reg_Reg_Right_Reg_Right_Reg_Right_Right_Reg_Right_Reg_Right_Reg_Right_Reg_Right) S10 for correcting the lo point and hi point of G
7; otherwise, proceed to S112.

Basically, the hi point of G is set to the formula (3) so that the target distribution width is obtained by aligning G with the lo point of R.
It is calculated by (4). However, when the original G distribution is out of the distribution determined by the equations (3) and (4), the lo point hi is set so that the original G distribution is included.
Shift the points to respond.

G_lo = R_lo (3) G_hi = G_lo + set_range_G (4) In S107, the magnitudes of G_lo and R_lo are compared in order to determine whether the original distribution protrudes at the lo point of the new distribution. Does not protrude at lo point (G_lo> R
If it is determined to be (_lo), the size of G_hi and (R_lo + set_range_G) are compared in S108 to determine whether the original distribution protrudes at the hi point of the new distribution. not protruding at hi point (G_
When it is determined that hi <(R_lo + set_range_G), G_lo is updated in S109 and G_hi is updated in S111. at the hi point (G
When it is determined that _hi ≧ (R_lo + set_range_G), in step S110, G_lo is updated according to equation (5), and G_hi is not updated.

G_lo = G_hi-set_range_G (5) If it is determined that the point protrudes from the lo point (G_lo ≦ R_lo), the G_lo is not updated, and only the G_hi is updated in S111. Up to this point, the updating of the lo point and the hi point of G based on R has been described.

In S112, the distribution width B_range of B is equal to the target distribution width set_range_B calculated in S105.
If it is smaller, the process proceeds to S113 for correcting the lo point and the hi point of B. Otherwise, the process proceeds to end, and this process ends.

In the case of B, similarly to the case of G, B is set to lo
The hi point of B is calculated by the equations (6) and (7) so that the target distribution width is aligned with the point. However, when the original distribution of B is out of the distribution determined by the equations (6) and (7), the lo point and the hi point are shifted so that the original distribution of B is included.

B_lo = R_lo (6) B_hi = B_lo + set_range_B (7) In S113, the sizes of B_lo and R_lo are compared in order to determine whether the original distribution protrudes from the lo point of the new distribution. Does not protrude at lo point (B_lo> R
If it is determined to be (_lo), the size of B_hi and (R_lo + set_range_B) are compared in S114 to determine whether the original distribution protrudes at the hi point of the new distribution. Does not protrude at hi point (B_
When it is determined that hi <(R_lo + set_range_B), the B_lo is updated in S115 and the B_hi is updated in S117. protruding at hi point (B
When it is determined that _hi ≧ (R_lo + set_range_B), in step S116, B_lo is updated by the equation (8), and B_hi is not updated.

B_lo = B_hi-set_range_B (8) If it is determined that the point protrudes from the lo point (B_lo ≦ R_lo), the B_lo is not updated, and only the B_hi is updated in S117. Up to this point, the updating of the lo point and the hi point of B based on R is described.

In S118, G_range = range
If _max, the flow shifts to step S119 to perform contrast correction based on G;
Is performed on the basis of.

In S119, G which is range_max
The distribution width ratio of R and B to _range is target
The target distribution width for obtaining the same value as t_rate is calculated by the following equation.

Set_range_R = (range_max * range_limit_R) / range_limit_G (9) set_range_B = (range_max_range_limit_B of (range_range_limit_B) / range_Reg_Rite_Reg_Register_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Right_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Right_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Right_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg) S12 for correcting the lo point and hi point of R
Then, the process proceeds to S126.

As in the case of the R reference, the R hi point is calculated by the formulas (11) and (12) so that R is aligned with the G lo point to obtain the target distribution width. However, when the original R distribution is out of the distribution determined by the equations (11) and (12), the lo point and the hi point are shifted so that the original R distribution is included.

R_lo = G_lo (11) R_hi = R_lo + set_range_R (12) In S121, the sizes of R_lo and G_lo are compared in order to determine whether the original distribution protrudes from the lo point of the new distribution. Does not protrude at lo point (R_lo> G
If it is determined to be (_lo), the size of R_hi and (G_lo + set_range_R) are compared in S122 to determine whether the original distribution protrudes at the hi point of the new distribution. not protruding at hi point (R_
When it is determined that hi <(G_lo + set_range_R), the R_lo is updated in S123 and the R_hi is updated in S125. at the hi point (R
If it is determined that _hi ≧ (G_lo + set_range_R), R_lo is determined in step S124 according to equation (13).
, And R_hi is not updated.

R_lo = R_hi-set_range_R (13) When it is determined that the data protrudes from the lo point (R_lo ≦ G_lo), the R_lo is not updated, and only the R_hi is updated in S125. Up to this point, the lo point and hi point of R are updated based on G.

In S126, the distribution width B_range of B is equal to the target distribution width set_range_B calculated in S119.
If it is smaller, the process shifts to S127 for correcting the lo point and the hi point of B. If not, the process shifts to end, and this process ends.

In the case of B, similarly to the case of R, B is
The hi point of B is calculated by the formulas (14) and (15) so that the target distribution width is aligned with the point. However, when the original distribution of B is out of the distribution determined by the equations (14) and (15), the lo point and the hi point are shifted so that the original distribution of B is included.

B_lo = G_lo (14) B_hi = B_lo + set_range_B (15) In S127, the magnitudes of B_lo and G_lo are compared to determine whether the original distribution protrudes from the lo point of the new distribution. Does not protrude at lo point (B_lo> G
If it is determined to be (_lo), the size of B_hi and (G_lo + set_range_B) are compared in S128 to determine whether the original distribution protrudes at the hi point of the new distribution. Does not protrude at hi point (B_
When it is determined that hi <(G_lo + set_range_B)), B_lo is updated in S129 and B_hi is updated in S131. protruding at hi point (B
If it is determined that _hi ≧ (G_lo + set_range_B), it is determined in step S130 that B_lo is obtained from the expression (16).
Is updated, and B_hi is not updated.

B_lo = B_hi-set_range_B (16) If it is determined that the point protrudes from the lo point (B_lo ≦ G_lo), the B_lo is not updated, and only the B_hi is updated in S131. Up to this point, the updating of the lo point and the hi point of B on the basis of G is described.

In and after S132, contrast correction based on B is performed. In S132, the distribution width ratio of R and G is set to tar with respect to B_range which is range_max.
The target distribution width for obtaining the same value as get_rate is calculated by the following equation.

Set_range_R = (range_max * range_limit_R) / range_limit_B (17) set_range_G = (Range_max_range_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Reg_Right_Reg_Reg_Reg_Reg_Right_Reg_Right_Reg_Right_Reg_Right_Right_Reg_Right_Right_Reg_Right_Reg_Right_Reg_Right_Reg_Right_Reg_Right_Reg_Right_Reg_Right_Right_Right_Right_Range) To correct the lo point hi point of R
Then, the process proceeds to S139.

As in the case of the R and G standards, R is
HI of R so that it becomes the target distribution width in line with the o point
Points are calculated by equations (19) and (20). However, when the original R distribution is out of the distribution determined by the equations (19) and (20), the lo point and the hi point are shifted so that the original R distribution is included.

R_lo = B_lo (19) B_hi = R_lo + set_rangeR (20) In S134, the magnitudes of R_lo and B_lo are compared in order to determine whether the original distribution protrudes from the lo point of the new distribution. Does not protrude at lo point (R_lo> B
If it is determined to be (_lo), the size of R_hi and (B_lo + set_range_R) are compared in S135 to determine whether the original distribution protrudes at the hi point of the new distribution. not protruding at hi point (R_
When it is determined that hi <(B_lo + set_range_R), the R_lo is updated in S136 and the R_hi is updated in S138. at the hi point (R
If it is determined that _hi ≧ (B_lo + set_range_R), R_lo is determined in step S137 according to equation (21).
, And R_hi is not updated.

R_lo = R_hi-set_range_R (21) If it is determined that the point protrudes from the lo point (R_lo ≦ B_lo), the R_lo is not updated, and only the R_hi is updated in S138. Up to this point, the lo point and the hi point of R are updated based on B.

In S139, the distribution width G_range of G is equal to the target distribution width set_range_G calculated in S132.
If it is smaller, the process proceeds to S140 for correcting the lo point and the hi point of G, and if not, the process proceeds to end and the process ends.

In the case of G, similarly to the case of R, G is
The hi point of G is calculated by the equations (22) and (23) so that the target distribution width is obtained in line with the point. However, when the original G distribution is out of the distribution determined by the equations (22) and (23), the lo point and the hi point are shifted so that the original G distribution is included.

G_lo = B_lo (22) G_hi = G_lo + set_range_G (23) In S140, the magnitudes of G_lo and B_lo are compared to determine whether the original distribution protrudes from the lo point of the new distribution. Does not protrude at lo point (G_lo> B
If it is determined to be (_lo), the size of G_hi and (B_lo + set_range_G) are compared in S141 to determine whether the original distribution protrudes at the hi point of the new distribution. not protruding at hi point (G_
When it is determined that hi <(B_lo + set_range_G)), G_lo is updated in S142 and G_hi is updated in s144. at the hi point (G
If it is determined that _hi ≧ (B_lo + set_range_G), it is determined in step s143 that B_lo is obtained from equation (24).
, And G_hi is not updated.

G_lo = G_hi-set_range_G (24) When it is determined that the data protrudes from the lo point (G_lo ≦ B_lo), the G_lo is not updated, and only the G_hi is updated in S144. Up to this point, the lo point and the hi point of G are updated based on B.

According to the above-described method, when the distribution width ratio of the histogram of the multivalued image is out of the allowable ratio of the distribution width target ratio of each color determined by the histogram distribution, the upper limit value and the lower limit value of the histogram are reduced. Make changes.

In this embodiment, the lower limit of the distribution width for obtaining the target distribution width ratio is determined by the lower limit of the histogram distribution. However, the upper limit of the histogram distribution may be used, or the average value of the histogram distribution may be used. Alternatively, an intermediate point between the upper limit and the lower limit of the histogram distribution may be used.

Also, in the present embodiment, R is used as a multi-valued image.
Although each GB is 8 bits, it is not limited to 8 bits but is determined by the specifications of a system incorporating the present invention. For example, if the multi-valued image from the scanner is R
If the data is input in each of 12 bits of GB, the same effect as in the present embodiment can be obtained by setting the lower limit of the histogram distribution width in 12 bits.

According to the present embodiment, there is an effect that it is possible to perform contrast correction on an image having a biased color without disturbing the color balance.

Also, when a document having a wide dynamic range of exposure amount such as a negative film and having a non-linear characteristic is read as image data, the contrast correction amount is changed by changing the contrast correction amount according to the image exposure condition. I can do it. Therefore, even when a negative film is captured by a scanner, there is an effect that appropriate contrast correction can be performed.

(Other Embodiments) The present invention relates to:
The present invention may be applied to a system including a plurality of devices (for example, a host computer, an interface device, a reader, a printer, and the like), or may be applied to a device including one device (for example, a copier, a facsimile device, and the like). .

Further, an object of the present invention is to supply a storage medium (or a recording medium) in which a program code of software for realizing the functions of the above-described embodiment is recorded to a system or an apparatus, and to provide a computer (a computer) of the system or the apparatus. Alternatively, it is needless to say that the present invention can also be achieved by a CPU or an MPU) reading and executing the program code stored in the storage medium. In this case, the program code itself read from the storage medium implements the functions of the above-described embodiment, and the storage medium storing the program code constitutes the present invention. Also,
When the computer executes the readout program code, not only the functions of the above-described embodiments are realized, but also the operating system (OS) running on the computer based on the instructions of the program code.
It goes without saying that a case where the functions of the above-described embodiments are implemented by performing some or all of the actual processing, and the processing performs the functions of the above-described embodiments.

Further, after the program code read from the storage medium is written into a memory provided in a function expansion card inserted into the computer or a function expansion unit connected to the computer, the program code is read based on the instruction of the program code. Needless to say, the CPU included in the function expansion card or the function expansion unit performs part or all of the actual processing, and the processing realizes the functions of the above-described embodiments.

When the above embodiment is applied to a storage medium, the storage medium stores program codes corresponding to the above-described flowcharts (shown in FIGS. 1A to 1D).

[0074]

According to the present invention, it is possible to provide an image processing method and apparatus capable of performing contrast correction corresponding to color deviation.

[Brief description of the drawings]

FIG. 1A is a flowchart illustrating a flow of a contrast correction process according to an embodiment of the present invention;

FIG. 1B is a flowchart showing a flow of a contrast correction process as one embodiment of the present invention.

FIG. 1C is a flowchart illustrating the flow of a contrast correction process according to an embodiment of the present invention.

FIG. 1D is a flowchart showing a flow of a contrast correction process as one embodiment of the present invention.

FIG. 2 is a flowchart illustrating a flow of image processing for determining color bias and correcting a gradation width.

FIG. 3 shows an example of a histogram of an image having a color bias and R
FIG. 13 is a diagram showing an example of updating the lower limit and upper limit of G and B based on.

FIG. 4 is a diagram showing a distribution width lower limit value according to a histogram lower limit value.

FIG. 5 is a diagram showing a contrast correction table.

FIG. 6 is a flowchart showing a flow of a conventional contrast correction process.

──────────────────────────────────────────────────の Continued on the front page (51) Int.Cl. 7 Identification symbol FI Theme coat ゛ (Reference) H04N 9/64 H04N 1/40 101E 9/69 1/46 Z F term (Reference) 5B057 AA20 BA02 BA30 CA01 CA08 CA12 CA16 CB01 CB08 CB12 CB16 CC01 CE11 CE17 DA17 DB02 DB06 DB09 DC23 DC25 5C026 CA02 CA15 5C066 AA01 AA11 CA08 EA03 EA07 EB01 EC05 GA01 GA05 GB01 JA03 KD06 KE07 KE11 KP02 5C077 LL19 MP081927 PP15 PA01 PA02 PA03

Claims (11)

    [Claims]
  1. An image processing method for processing a multi-tone image of a plurality of colors, comprising the steps of comparing the characteristics of the luminance frequency distribution of the image for each color to determine whether there is a color bias. An image processing method comprising: performing a contrast correction based on a correlation between luminance frequency distributions of respective colors when it is determined in the determining step that there is a color bias.
  2. 2. The method according to claim 1, wherein the determining step includes: generating a luminance frequency distribution from image data; determining a distribution width of the luminance frequency distribution for each color; and determining a distribution width ratio of each color from the distribution width. A target ratio deriving step of obtaining a distribution width target ratio of each color from the characteristics of the luminance frequency distribution; and determining that there is a color bias when the distribution width ratio deviates from the distribution width target ratio by a predetermined value or more. The image processing method according to claim 1, further comprising:
  3. 3. The target ratio deriving step may include any one of a lower limit luminance value, an upper limit luminance value, an average luminance value, an intermediate value between a lower limit luminance value and an upper limit luminance value in the luminance frequency distribution, or a combination thereof. 3. The image processing method according to claim 2, further comprising the step of obtaining the distribution width target ratio according to the following.
  4. 4. The method according to claim 1, wherein said correcting step includes a step of changing a maximum gradation width of another color based on a maximum gradation width of any one color. Image processing method.
  5. 5. The correcting step comprises changing an upper limit value and / or a lower limit value of a maximum gradation width of each color,
    5. The image processing method according to claim 1, further comprising a step of setting a distribution width ratio of each color equal to the distribution width target ratio.
  6. 6. An image processing apparatus for processing a multi-tone image of a plurality of colors, comprising: comparing a characteristic of a luminance frequency distribution of an image of each color to determine whether or not there is a color bias; An image processing apparatus comprising: a correction unit configured to perform contrast correction based on a correlation between luminance frequency distributions of respective colors when the determination unit determines that there is a color bias.
  7. 7. A generating means for generating a luminance frequency distribution from image data, a distribution width deriving means for obtaining a distribution width of the luminance frequency distribution for each color, a distribution width ratio of each color from the distribution width. A distribution width ratio deriving unit that obtains, and a target ratio deriving unit that obtains a distribution width target ratio of each color from the characteristics of the luminance frequency distribution. The image processing apparatus according to claim 6, further comprising: a determination unit configured to determine that there is a color bias.
  8. 8. The target ratio deriving means, wherein one of a lower limit luminance value, an upper limit luminance value, an average luminance value, an intermediate value between a lower limit luminance value and an upper limit luminance value in the luminance frequency distribution, or a combination thereof. The image processing apparatus according to claim 7, further comprising a unit that calculates the distribution width target ratio in accordance with the following.
  9. 9. The apparatus according to claim 6, wherein said correction means includes means for changing a maximum gradation width of another color based on a maximum gradation width of any one color. Image processing device.
  10. 10. The correction means changes an upper limit value and / or a lower limit value of a maximum gradation width of each color,
    The image processing apparatus according to claim 6, further comprising a unit configured to make a distribution width ratio of each color equal to the distribution width target ratio.
  11. 11. A computer-readable memory storing an image processing program for processing a multi-tone image of a plurality of colors, the image processing program comparing characteristics of a luminance frequency distribution of an image for each color, and A code for a determination step of determining whether or not there is a bias; and a correction step of performing contrast correction based on the correlation between the luminance frequency distributions of the respective colors when the determination step determines that there is a color bias. And a computer readable memory comprising:
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7330600B2 (en) 2002-09-05 2008-02-12 Ricoh Company, Ltd. Image processing device estimating black character color and ground color according to character-area pixels classified into two classes
KR100871686B1 (en) 2002-08-23 2008-12-05 삼성전자주식회사 Adaptive contrast and brightness enhancement method and apparatus for color preserving

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR100871686B1 (en) 2002-08-23 2008-12-05 삼성전자주식회사 Adaptive contrast and brightness enhancement method and apparatus for color preserving
US7330600B2 (en) 2002-09-05 2008-02-12 Ricoh Company, Ltd. Image processing device estimating black character color and ground color according to character-area pixels classified into two classes

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