CN111292246A - Image color correction method, storage medium, and endoscope - Google Patents
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Abstract
An image color correction method, a storage medium, and an endoscope, the image color correction method including: shooting a standard color card by using a system to be corrected to obtain R, G, B values to be corrected of n color blocks in the color card and L, M, N values to be corrected of each component of a color model; establishing an inequality constraint function; correcting the values to be corrected R, G, B of the n color blocks in the standard color card according to the color correction matrix coefficient X to obtain a corrected matrix; obtaining each component value L of the converted color model1、M1、N1(ii) a Component standard value L according to color model in standard color cardb、Mb、NbAnd the component values L of the converted color model1、M1、N1Establishing an objective function; fitting the target function to obtain the color according to the constraint function and the target function under the condition that the value of the target function is minimumThe color correction matrix coefficients X. The method is simple and convenient, avoids a complex image data analysis process, and can correct the image color according to actual needs.
Description
Technical Field
The present invention relates to the field of image processing, and in particular, to an image color correction method, a storage medium, and an endoscope.
Background
With the development of computer science and color input and output technology, color images as information carriers are increasingly widely used in many fields such as printing, movie and television, advertisement, electronic commerce and digital entertainment, and the requirements of people on color reproduction quality are also increasingly high. However, in the process of acquiring a color image by an imaging system such as a camera, the color of the captured image may deviate from the color of the real object, and in order to reduce the deviation, color correction is generally performed on the image captured by the image capturing apparatus.
In the method of image color correction, the most basic RGB (red, green and blue) color space is generally converted into other color spaces suitable for calculation adjustment, such as HSI (hue, saturation and intensity) color space, HSV (hue, saturation and brightness), YUV (brightness, chroma and concentration) color space, Lab color space, and the like, and then adjusted. However, the adjustment method is cumbersome and requires complicated image data analysis.
Disclosure of Invention
The invention aims to provide an image color correction method, a storage medium and an endoscope. The image color correction method is simple and convenient, avoids a complex image data analysis process, and can correct the image color according to actual needs.
The invention provides an image color correction method, which comprises the following steps:
s1: shooting a standard color card by using a system to be corrected to obtain R, G, B values to be corrected of n color blocks in the color card and L, M, N values to be corrected of each component of a color model;
s2: establishing an inequality constraint function: the | A X-B | is less than or equal to K, wherein,
r, G, B is the value to be corrected of n color blocks in the standard color card;
Rb、Gb、Bbthe standard numerical values of n color blocks in the standard color card are shown; x is the coefficient of the color correction matrix,
s3: correcting the values to be corrected R, G, B of the n color blocks in the standard color card according to the color correction matrix coefficient X to obtain a corrected matrix:
s4: according to the corrected matrix
And converting the RGB into each component of the color model to obtain each component value L of the converted color model1、M1、N1；
S5: component standard value L according to color model in standard color cardb、Mb、NbAnd the component values L of the converted color model1、M1、N1Establishing an objective function, and enabling the objective function f to be equal to the sum of root-mean-square differences between each standard component value in the n color cards and the component value of the corresponding converted color model:
s6: and fitting the target function under the condition of the minimum value of the target function according to the constraint function and the target function to obtain a color correction matrix coefficient X, and correcting the image color according to the color correction matrix coefficient X.
Further, in step S5, the method further includes increasing the weight of each component in the color model on the root mean square of the difference value between each standard component value and the corresponding component of the converted color model:
wherein k is1、k2And k3Weight coefficient, k, for root mean square of each difference1、k2And k3Are real numbers.
Further, the method further comprises setting, in the objective function, weights of required components highlighting required patches in the standard color patch:
wherein, i represents the serial number of the color block required in the selected standard color card; o represents a component of the color model that needs to be highlighted, which may be one or more of L, M and N; k is a radical of4Denotes the weight, k, of the ith patch4Are real numbers.
Further, the method further comprises the steps of carrying out a color correction test according to the obtained color correction matrix coefficient X after obtaining the color correction matrix coefficient X, and adjusting the weight of the root mean square of the difference value of each component according to the test result.
Further, the color model is an HSI color model, an HSL color model, a YUV color model, or a Lab color model.
Further, in step S4, the obtained corrected matrix is converted into each component value L of the color model by a geometric derivation method, a coordinate conversion algorithm, a segmentation definition method, a Bajon approximation algorithm, or a standard model method1、M1、N1。
Further, fitting the objective function by a least square method or linear regression to obtain the color correction matrix coefficient X according to the constraint function and the objective function under the condition that the value of the objective function is minimum.
Further, the sum of each column of the color correction matrix coefficients X goes to 1.
The present invention also provides a computer storage medium including a computer program which, when executed, implements the image color correction method provided by the present invention. .
The invention also provides an endoscope, and the image color correction method provided by the invention is adopted to carry out color correction on the image.
In summary, the present invention photographs the standard color card through the coefficient to be corrected to obtain R, G, B to be corrected in the standard color card and each component of the color model, and at the same time, establishes the constraint function according to the standard value of the RGB component in the standard color card and the value to be measured of RGB, establishes the objective function according to the sum of the root mean square of the difference values of the standard component of the same component in each color card and the converted component, and fits the objective function and the constraint function to obtain the color correction matrix coefficient, so that the sum of each column of the color correction matrix coefficient X tends to 1. Compared with the existing correction method based on image color distribution characteristics, color space mapping and spectral reflectivity restoration, the method is simple and convenient, avoids a complex image data analysis process, and can replace a target function and constraint in real time according to actual requirements to obtain a color correction coefficient meeting the requirements.
The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical means of the present invention more clearly understood, the present invention may be implemented in accordance with the content of the description, and in order to make the above and other objects, features, and advantages of the present invention more clearly understood, the following preferred embodiments are described in detail with reference to the accompanying drawings.
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Fig. 1 is a schematic control flow diagram of an image color correction method according to the present invention.
Detailed Description
To further explain the technical means and effects of the present invention adopted to achieve the predetermined objects, the present invention will be described in detail below with reference to the accompanying drawings and preferred embodiments.
The invention aims to provide an image color correction method, a storage medium and an endoscope. The image color correction method is simple and convenient, avoids a complex image data analysis process, and can correct the image color according to actual needs.
It should be noted that the color model mentioned in the present invention refers to other color spaces suitable for computer calculation adjustment besides RGB (Red, Green, Blue) color model, such as HSI (Hue, Saturation, brightness) color model, HSL (Hue, Saturation, brightness) color model, YUV (Lightness, Chroma) color model, Lab color model, etc.
Fig. 1 is a schematic control flow diagram of an image color correction method provided by the present invention, and as shown in fig. 1, the automatic exposure control method provided by the present invention includes the following steps:
s1: the standard color card is photographed by a system to be corrected, so as to obtain the values to be corrected of R, G, B of n color blocks in the color card, and the values to be corrected of each component L, M, N of the color model (L, M, N refers to each component in the color model, which is not limited to three here, and may include other components according to the definition of the color model). Wherein, n may represent all color blocks in the standard color card, or may be a part selected according to the requirement, such as 12 color blocks. The system to be corrected comprises a camera device which can be used for shooting the color card.
S2: establishing an inequality constraint function: and | A X-B | is less than or equal to K.
Wherein, A is the value to be corrected R, G, B of n color blocks in the standard color card; b is the standard value R of n color blocks in the standard color cardb、Gb、Bb(ii) a X is a color correction matrix coefficient; the inequality constraint K depends on the requirements of the actual model, and the difference of K values can cause the difference of the color correction matrix coefficients X. Namely:
S3: correcting the values to be corrected R, G, B of the n color blocks in the standard color card according to the color correction matrix coefficient X to obtain a corrected matrix:
s4: according to the corrected matrix
And converting the RGB into each component of the color model to obtain each component value L of the converted color model1、M1、N1. The RGB to color model components conversion algorithm may be, but not limited to, geometric derivation, coordinate transformation, segmentation definition, Bajon approximation, or standard model algorithm.
S5: component standard value L according to color model in standard color cardb、Mb、NbAnd the component values L of the converted color model in the color model1、M1、N1And establishing an objective function, and enabling the objective function f to be equal to the sum of root-mean-square differences between each standard component value in the n color cards and the component value of the corresponding converted color model.
Further, in order to better meet the actual requirement, a weight coefficient of each component in each color model may be added before each root mean square of the difference values to highlight a certain component, that is, the objective function f at this time is:
wherein k is1、k2And k3Weight coefficient, k, for root mean square of each difference1、k2And k3Are real numbers.
Further, the objective function may also be set to highlight a desired component in a desired color block in the standard color card, such as the color of the ith color block, in this case, the objective function f may be:
wherein i represents the serial number of the color block required in the selected standard color card, and O represents the component to be highlighted in the color model, which may be one or more of L, M and N; k is a radical of4Denotes the weight, k, of the ith patch4Are real numbers.
S6: and fitting the target function according to the constraint function and the target function under the condition that the value of the target function is minimum to obtain a color correction matrix coefficient X. The fitting method may be, but is not limited to, least squares, nonlinear regression, unconstrained nonlinear fitting function, or nonlinear fitting with constrained conditions, etc.
S7: and carrying out a color correction test according to the obtained color correction matrix coefficient X, and adjusting the weight of the difference root mean square of each component according to the test result. After the image is corrected by using the color correction matrix coefficient X, if the corrected image is not satisfactory, the weight of the root mean square of the difference value of each component in the objective function f can be finely adjusted, for example, the component of a certain color block is added, and the fine adjustment is performed on the premise that the result of the objective function f is not changed greatly.
In this embodiment, the standard color card is photographed by the coefficient to be corrected to obtain R, G, B to be corrected and each component of the color model in the standard color card, meanwhile, a constraint function is established according to the standard value of the RGB component in the standard color card and the value to be measured of RGB, an objective function is established according to the sum of the root mean square of the difference values of the standard component of the same component in each color card and the converted component, a color correction matrix coefficient is obtained by fitting the objective function and the constraint function, and the color is corrected by the color correction matrix coefficient, which can change the RGB color model which is not suitable for computer processing into other color models which are more suitable for calculation processing, compared with the existing correction method based on image color distribution characteristics, color space mapping and spectral reflectance restoration, the method is simple and convenient, and avoids a complicated image data analysis process, meanwhile, the objective function and the constraint can be replaced in real time according to actual requirements, and the color correction coefficient meeting the requirements is obtained.
The color correction method provided by the present invention is explained in more detail below with an HSI (Hue, Saturation, brightness) color model.
S1: by shooting the standard color card with the system to be corrected, the values to be corrected of R, G, B of the n color patches in the color card and the values to be corrected of each component H, S, I of the color model are obtained, in this embodiment, n may be 12, that is, 12 color patches of the standard color card are taken.
S2: establishing an inequality constraint function: i A X-B I is less than or equal to K, wherein A is the value to be corrected R, G, B of n color blocks in the standard color card; b is the standard value R of n color blocks in the standard color cardb、Gb、Bb(ii) a X is a color correction matrix coefficient; the inequality constraint K depends on the requirements of the actual model, and the difference of K values can cause the difference of the color correction matrix coefficients X.
For example, if the value to be corrected of the 2 nd color block in the standard color card is: r is 139, G is 11, B is 6; at this time, a ═ 139116 ], it can be understood that since in the present embodiment, 12 color patches are selected from the standard color card, at this time, a should be a 12 × 3 matrix; similarly, if the standard value of the 2 nd color block in the standard color card is 179, 42 and 50, then B is [ 1794250 ], and for the same reason, B is also a 12 × 3 matrix.
S3: the number to be corrected of 12 color blocks in the standard color card is calculated according to the color correction matrix coefficient XThe value R, G, B is corrected to obtain a corrected matrix:
s4: after obtaining the corrected matrix, H, S and I values are obtained according to the conversion formula from RGB to HSI, which may be, but not limited to, geometric derivation method, coordinate transformation algorithm, segmentation definition method, Bajon approximation algorithm or standard model method. Taking geometric derivation as an example:
s5: defining the H value after conversion to HSI color space as 1 × 12 matrix H1The value of S is a 1 × 12 matrix S1And L is a 1 × 12 matrix L1. To obtain the objective function:
in this case, the weight of a certain component may be specified. If the hue requirement is high, and the luminance component does not need to make a requirement, the weight of the H component may be high, the weight of the H component is 0.7, the weight of the S component is 0.3, and the weight of the L component is 0, that is, the objective function obtained at this time is:
it is understood that if the saturation requirement is high, the weight of the S component can be increased.
If the requirement for brightness is higher and the requirement for a certain color, such as red, needs to be raised, the weight of the red color block can be increased, if the red color block is the 3 rd color block of the selected standard color blocks, the weight given by the color block is 0.4, the weight of H is 0.5, and the weight of S is 0.1, then the objective function can be obtained:
s6: after an inequality constraint function and an objective function are established, the objective function is fitted according to the constraint function and the objective function under the condition that the value of the objective function is minimum, and the color correction matrix coefficient X is obtained.
It is understood that in this step, the method of fitting may be selected as desired, such as least squares or non-linear regression.
After obtaining the color correction matrix coefficient X, carrying out a correction test on the color according to the color correction matrix coefficient X, and carrying out a root mean square weight k on the difference value of each component according to the test result1、k2、k3And k4Fine tuning is performed to obtain the most desirable results.
In summary, the present invention shoots a standard color card through a coefficient to be corrected to obtain R, G, B to be corrected and each component of a color model in the standard color card, establishes a constraint function according to a standard value of an RGB component in the standard color card and a value to be measured of RGB, establishes an objective function according to a sum of root-mean-square differences between the standard component of the same component in each color card and the converted component, fits the objective function and the constraint function to obtain a color correction matrix coefficient X, and corrects colors by using the color correction matrix coefficient X, which can change an RGB color model unsuitable for computer processing into another color model more suitable for computational processing, compared with the existing correction method based on image color distribution characteristics, color space mapping and spectral reflectance restoration, the method is simple and convenient, and avoids a complicated image data analysis process, meanwhile, the objective function and the constraint can be replaced in real time according to actual requirements, and the color correction coefficient meeting the requirements is obtained.
The present invention also provides a computer storage medium including a computer program that, when executed, implements the image color correction method provided by the present invention.
The invention also provides an endoscope, which adopts the image color correction method provided by the invention to correct the image color.
Although the present invention has been described with reference to a preferred embodiment, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. An image color correction method characterized by: the method comprises the following steps:
s1: shooting a standard color card by using a system to be corrected to obtain R, G, B values to be corrected of n color blocks in the color card and L, M, N values to be corrected of each component of a color model;
s2: establishing an inequality constraint function: the | A X-B | is less than or equal to K, wherein,
r, G, B is the value to be corrected of n color blocks in the standard color card;
Rb、Gb、Bbthe standard numerical values of n color blocks in the standard color card are shown; x is the coefficient of the color correction matrix,
s3: correcting the values to be corrected R, G, B of the n color blocks in the standard color card according to the color correction matrix coefficient X to obtain a corrected matrix:
s4: according to the corrected matrix
And converting the RGB into each component of the color model to obtain each component value L of the converted color model1、M1、N1；
S5: component standard value L according to color model in standard color cardb、Mb、NbAnd the component values L of the converted color model1、M1、N1Establishing an objective function, and enabling the objective function f to be equal to the sum of root-mean-square differences between each standard component value in the n color cards and the component value of the corresponding converted color model:
s6: and fitting the target function according to the constraint function and the target function under the condition that the value of the target function is minimum to obtain a color correction matrix coefficient X.
2. The image color correction method according to claim 1, characterized in that: in step S5, the method further includes increasing the weight of each component in the color model at the root mean square of the difference value between each standard component value and the corresponding component of the converted color model:
wherein k is1、k2And k3Weight coefficient, k, for root mean square of each difference1、k2And k3Are real numbers.
3. The image color correction method according to claim 2, characterized in that: the method also comprises the following steps of setting the weight of the required components for highlighting the required color blocks in the standard color card in the objective function:
wherein, i represents the serial number of the color block required in the selected standard color card; o represents the component of the color model that needs to be highlighted, which is one or more of L, M and N; k is a radical of4Denotes the weight, k, of the ith patch4Are real numbers.
4. The image color correction method according to claim 1, characterized in that: the method also comprises the steps of carrying out a color correction test according to the obtained color correction matrix coefficient X after obtaining the color correction matrix coefficient X, and adjusting the weight of the root mean square of the difference value of each component according to the test result.
5. The image color correction method according to claim 1, characterized in that: the color model is an HSI color model, an HSL color model, a YUV color model or a Lab color model.
6. The image color correction method according to claim 1, characterized in that: in step S4, the corrected matrix is converted into each component value L of the color model by a geometric derivation method, a coordinate conversion algorithm, a segment definition method, a Bajon approximation algorithm, or a standard model method1、M1、N1。
7. The image color correction method according to claim 1, characterized in that: and fitting the target function by a least square method or linear regression to obtain the color correction matrix coefficient X under the condition of the minimum value of the target function according to the constraint function and the target function.
8. The image color correction method according to claim 1, characterized in that: the sum of each column of the color correction matrix coefficients X goes to 1.
9. A computer storage medium, characterized in that: the computer storage medium includes a computer program that, when executed, implements the image color correction method of any one of claims 1 to 8.
10. An endoscope, characterized by: the image color correction method according to any one of claims 1 to 8 is employed.
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