CN110505459B - Image color correction method, device and storage medium suitable for endoscope - Google Patents
Image color correction method, device and storage medium suitable for endoscope Download PDFInfo
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- CN110505459B CN110505459B CN201910760188.2A CN201910760188A CN110505459B CN 110505459 B CN110505459 B CN 110505459B CN 201910760188 A CN201910760188 A CN 201910760188A CN 110505459 B CN110505459 B CN 110505459B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/10—Cameras or camera modules comprising electronic image sensors; Control thereof for generating image signals from different wavelengths
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/80—Camera processing pipelines; Components thereof
- H04N23/84—Camera processing pipelines; Components thereof for processing colour signals
- H04N23/88—Camera processing pipelines; Components thereof for processing colour signals for colour balance, e.g. white-balance circuits or colour temperature control
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N9/00—Details of colour television systems
- H04N9/64—Circuits for processing colour signals
Abstract
The invention discloses an image color correction method, device and storage medium suitable for an endoscope, wherein the method comprises the following steps: acquiring a gray scale image of a current frame image acquired by a camera of an endoscope in real time; calculating the ratio of the first type of pixels in the gray-scale image; the first type of pixels are pixels with gray values larger than or equal to a gray threshold value; and judging whether the ratio is greater than or equal to a preset ratio, if so, performing white balance processing on the current frame image by adopting a preset white balance adjustment algorithm to obtain a current frame image after color correction, and if not, correcting the color of the current frame image according to the color correction parameter of the camera of the endoscope to obtain the current frame image after color correction. The invention can carry out color correction on the image collected by the endoscope in real time in the using process of the endoscope, so that the color of the image approaches to the real color, thereby reducing the color cast of the image.
Description
Technical Field
The invention relates to the technical field of medical instruments, in particular to an image color correction method and device suitable for an endoscope and a storage medium.
Background
An endoscope is a common medical instrument, which integrates traditional optics, ergonomics, precision machinery, modern electronics, mathematics, software and the like. With the continuous progress of medical technology, the clinical needs of endoscopes are further expanded and deepened, and the endoscopes become indispensable instruments in disease diagnosis and treatment. Due to the limitation of the irradiation condition of the endoscope with the light source and the complexity of the internal environment structure of the human body, the image collected by the endoscope can be dark in a large area due to insufficient exposure, and a doctor cannot normally observe the operation space in the operation, so that diagnosis errors and even operation failure can be caused. In addition, in the process of performing heat treatment on a focus while using an endoscope, the treatment light can cause the image acquired by the endoscope to generate great color deviation, and the great influence is caused on the observation of the condition of a patient in the operation process and the evaluation of the focus treatment after the operation. Therefore, it is very important to realize color correction of the endoscopic image.
At present, the conventional endoscope is configured with a manual white balance function, and generally, before a disease is diagnosed by using the endoscope, a piece of lightless white paper is placed in a room, a camera of the endoscope is aligned with the white paper, a picture is full, and the manual white balance function is executed to adjust image color cast.
The inventor finds that, in the process of implementing the invention, because the manual white balance function is only effective under the light source at the time of setting, when the ambient light source is changed, the image collected by the endoscope has larger color cast, the endoscope is used for collecting images in the human body, the light of the internal environment of the human body has larger difference with the light of the indoor environment, and the white balance effect can be interfered after the brightness adjusting function of part of the endoscope is started, so that the image collected by the endoscope in real time in the human body still has larger color cast even if the white balance is preset under the light source of the indoor environment.
Disclosure of Invention
The embodiment of the invention provides an image color correction method, device and storage medium suitable for an endoscope, which can perform color correction on an image acquired by the endoscope in real time in the using process of the endoscope, so that image color cast is reduced.
In order to achieve the above object, an embodiment of the present invention provides an image color correction method suitable for an endoscope, including:
acquiring a gray scale image of a current frame image acquired by a camera of an endoscope in real time;
calculating the ratio of the first type of pixels in the gray-scale image; the first type of pixels are pixels with gray values larger than or equal to a gray threshold value;
and judging whether the ratio is greater than or equal to a preset ratio, if so, performing white balance processing on the current frame image by adopting a preset white balance adjustment algorithm to obtain a current frame image after color correction, and if not, correcting the color of the current frame image according to the color correction parameter of the camera of the endoscope to obtain the current frame image after color correction.
As an improvement of the above scheme, the acquiring a gray scale image of a current frame image acquired by a camera of an endoscope in real time specifically includes:
copying a current frame image acquired by a camera of an endoscope in real time to obtain a copied image;
performing Gaussian smoothing processing on the copied image to obtain a processed copied image;
and converting the processed copy image into a gray-scale image.
As an improvement of the above scheme, the step of obtaining the gray threshold specifically includes:
acquiring an image of the N-order gray-scale image through a camera of the endoscope to obtain a test gray-scale image; wherein N is a positive integer;
acquiring the gray-scale value of each pixel in the test gray-scale image, and determining a reference gray-scale value according to the maximum gray-scale value and a preset percentage of the acquired gray-scale values of each pixel;
uniformly dividing the test gray-scale image into N areas, and calculating the average gray-scale value of each area according to the gray-scale value of each pixel in the test gray-scale image;
determining the smaller value and the larger value which are closest to the reference gray-scale value in the mean gray-scale value of each area;
and carrying out interpolation calculation according to the reference gray scale value, the smaller value and the larger value to obtain a gray scale corresponding to the reference gray scale value, and taking the gray scale corresponding to the reference gray scale value as the gray threshold value.
As an improvement of the above scheme, the preset white balance adjustment algorithm is a gray world algorithm;
performing white balance processing on the current frame image by using a preset white balance adjustment algorithm to obtain a color-corrected current frame image, specifically including:
determining a current gray level mean value parameter of a gray level world algorithm according to the gray level mean value of the first type of pixels;
and carrying out white balance processing on the current frame image by adopting a gray world algorithm and the current gray mean value parameter to obtain the current frame image after color correction.
As an improvement of the above scheme, the determining a current gray level mean parameter of a gray level world algorithm according to the gray level mean of the first-class pixels specifically includes:
calculating the gray average value of the first type of pixels;
trying to obtain a historical gray level mean parameter; the historical gray level mean value parameter is a gray level mean value parameter adopted when a gray level world algorithm is adopted to perform white balance processing on a previous frame of image;
if the historical gray level mean value parameter can be obtained, determining the current gray level mean value parameter according to the gray level mean value of the first type of pixels and the historical gray level mean value parameter;
and if the historical gray level mean value parameter cannot be acquired, determining a current gray level mean value parameter of a gray level world algorithm according to the gray level mean value of the first type of pixels.
As an improvement of the above scheme, the color correction parameters include a red component weighting coefficient, a green component weighting coefficient, and a blue component weighting coefficient;
correcting the color of the current frame image according to the color correction parameter of the camera of the endoscope to obtain the current frame image after color correction, specifically comprising:
acquiring three-channel components of the current frame image; wherein the three channel components include a red component, a green component, and a blue component;
multiplying the three-channel components by the weighting coefficients in the color correction parameters corresponding to the three-channel components respectively to obtain three-channel components adaptive to the camera;
and combining the three-channel components of the adaptive camera to obtain the current frame image after color correction.
As an improvement of the above scheme, the step of obtaining the color correction parameter specifically includes:
s1, acquiring images of the international standard color card through the camera of the endoscope to obtain a test color card image; the international standard color card comprises M color blocks, wherein M is a positive integer;
s2, calculating a red component gain coefficient, a green component gain coefficient and a blue component gain coefficient of the test color chart by adopting a gray world algorithm according to the RGB values of all pixels in the test color chart, and respectively setting the corresponding weighted values to be 1;
s3, adjusting the color value of the test color chart according to the red component gain coefficient, the green component gain coefficient, the blue component gain coefficient and the corresponding weighted value of the red component gain coefficient, the green component gain coefficient and the blue component gain coefficient of the test color chart to obtain the adjusted test color chart;
s4, calculating the Lab color space value of each color block in the adjusted test color chart;
s5, determining the chromaticity difference between the adjusted test color card chart and the international standard color card according to the Lab color space value of each color block and the international standard Lab color space value corresponding to the color block; wherein the chromaticity differences comprise a red-green chromaticity difference and a yellow-blue chromaticity difference;
s6, judging whether the chromaticity differences are all larger than a preset chromaticity difference threshold value, if so, executing a step S7, and if not, executing a step S8;
s7, modifying the weighted value of the gain coefficient of the red component or/and the weighted value of the gain coefficient of the blue component in the step S3 according to the chromaticity difference, and returning to the step S3;
s8, using the weighted value of the red component gain coefficient, the weighted value of the green component gain coefficient and the weighted value of the blue component gain coefficient in the step S3 as the red component weighting coefficient, the green component weighting coefficient and the blue component weighting coefficient in the color correction parameter, respectively.
Correspondingly, the embodiment of the invention also provides an image color correction device suitable for an endoscope, which comprises:
the acquisition module is used for acquiring a gray scale image of a current frame image acquired by a camera of the endoscope in real time;
the calculation module is used for calculating the ratio of the first type of pixels in the gray scale image; the first type of pixels are pixels with gray values larger than or equal to a gray threshold value;
and the correction module is used for judging whether the ratio is greater than or equal to a preset ratio or not, if so, performing white balance processing on the current frame image by adopting a preset white balance adjustment algorithm to obtain the current frame image after color correction, and if not, correcting the color of the current frame image according to the color correction parameter of the camera of the endoscope to obtain the current frame image after color correction.
Accordingly, an embodiment of the present invention further provides an image color correction apparatus suitable for an endoscope, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the image color correction method suitable for an endoscope according to any one of the above items when executing the computer program.
Accordingly, the embodiment of the present invention also provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program runs, the apparatus where the computer-readable storage medium is located is controlled to execute the image color correction method suitable for an endoscope according to any one of the above.
Compared with the prior art, the image color correction method, the image color correction device and the storage medium which are suitable for the endoscope provided by the embodiment of the invention are characterized in that firstly, a gray scale image of a current frame image which is acquired by a camera of the endoscope in real time is acquired; calculating the ratio of the first type of pixels in the gray-scale image; the first type of pixels are pixels with gray values larger than or equal to a gray threshold value; then, judging whether the ratio is greater than or equal to a preset ratio or not; if so, performing white balance processing on the current frame image by adopting a preset white balance adjustment algorithm to obtain a current frame image after color correction; if not, correcting the color of the current frame image according to the color correction parameter of the camera of the endoscope to obtain the current frame image after color correction, thereby realizing color correction on the image acquired by the endoscope in real time. According to the embodiment of the invention, the ratio of the pixels with the gray value larger than or equal to the gray threshold value in the current frame image collected by the camera of the endoscope is compared with the preset ratio, so that whether the current frame image is a light-tone image or a dark-tone image is determined, and therefore, the white balance processing can be correspondingly carried out on the current frame image by adopting the preset white balance adjusting algorithm according to the tone of the current frame image, or the color of the current frame image is corrected according to the color correction parameter of the camera of the endoscope, so that the color correction of the image collected by the endoscope is realized in real time, the color of the image approaches to the real color, and the color cast of the image can be accurately reduced.
Drawings
Fig. 1 is a schematic flow chart of an embodiment of an image color correction method suitable for an endoscope according to the present invention.
Fig. 2 is a flowchart illustrating an embodiment of step S300 in the image color correction method for an endoscope according to the present invention.
Fig. 3 is a schematic flowchart of another embodiment of step S300 in the image color correction method suitable for an endoscope according to the present invention.
Fig. 4 is a schematic structural diagram of an embodiment of an image color correction apparatus suitable for an endoscope according to the present invention.
Fig. 5 is a schematic structural diagram of another embodiment of the image color correction device suitable for the endoscope according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without any inventive step, are within the scope of the present invention.
Fig. 1 is a schematic flow chart of an embodiment of an image color correction method suitable for an endoscope according to the present invention.
The embodiment of the invention provides an image color correction method suitable for an endoscope, which comprises steps S100 to S300, and specifically comprises the following steps:
and S100, acquiring a gray scale image of the current frame image acquired by a camera of the endoscope in real time.
The method comprises the steps of collecting images in real time through a camera of an endoscope, and carrying out gray level processing on collected current frame images to obtain a gray level image.
S200, calculating the ratio of the first type of pixels in the gray-scale image; the first type of pixels are pixels with gray values larger than or equal to a gray threshold value.
And acquiring the gray value of each pixel in the gray image, and calculating the ratio of the pixels of which the gray values are greater than or equal to the gray threshold value in the gray image to all the pixels in the gray image so as to judge the tone of the image subsequently.
It can be understood that the gray scale value ranges from 0 to 255, which indicates that the brightness is from deep to light, the gray scale threshold is used to determine whether the pixel is a bright portion pixel, when the gray scale value of the pixel is greater than or equal to the gray scale threshold, the pixel is a bright portion pixel, and in specific implementation, the gray scale threshold may be selected according to actual situations, which does not affect the beneficial effects of the present invention.
S300, judging whether the ratio is larger than or equal to a preset ratio, if so, carrying out white balance processing on the current frame image by adopting a preset white balance adjustment algorithm to obtain the current frame image after color correction, and if not, correcting the color of the current frame image according to the color correction parameter of the camera of the endoscope to obtain the current frame image after color correction.
It can be understood that, for a general endoscopic channel, due to the light effect of the camera system, a plurality of bright spots of light spots exist in the collected image, and in addition, the edge and corner regions in a darker image may generate black edges to affect the viewing effect. The preset ratio is used for judging the tone of the image, when the ratio of the first type of pixels of the image is greater than or equal to the preset ratio, the image is indicated to be more bright pixels, namely the image is a bright tone image, when the ratio of the first type of pixels of the image is less than the preset ratio, the image is indicated to be less bright pixels, namely the image is a dark tone image, and in the specific implementation, the preset ratio can be selected according to the actual situation, so that the beneficial effects of the invention are not influenced.
When the ratio of the first type of pixels in the gray-scale image is obtained through calculation, comparing the ratio of the first type of pixels with a preset ratio, judging whether the ratio of the first type of pixels is larger than or equal to the preset ratio, if so, determining that the current frame image is a bright-tone image, and performing white balance processing on the current frame image by adopting a preset white balance adjustment algorithm to obtain the current frame image after color correction and displaying the current frame image; if not, determining that the current frame image is a dark-tone image, and correcting the color of the current frame image according to the color correction parameter of the camera of the endoscope, so as to obtain the color-corrected current frame image and display the color-corrected current frame image.
It should be noted that the preset white balance adjustment algorithm may be a gray world algorithm, a perfect reflection algorithm, a dynamic threshold algorithm, or other white balance adjustment algorithms, and may be selected according to actual conditions during specific implementation, without affecting the beneficial effects of the present invention. Optionally, the preset white balance adjustment algorithm is a gray world algorithm.
It should be noted that, because there is a color difference in the color processing of the camera, and the color correction parameter of the camera is used to correct the image color difference caused by the camera, the color of the current frame image is corrected by the color correction parameter of the camera of the endoscope, which can effectively reduce the image color cast.
Optionally, the preset ratio is obtained by the following method: making an original image of a 24-color contrast card in advance, covering 3 pixels by 3 pixels white small color blocks at 15 points of a color block boundary in the image, and storing the image as a first image; then, adopting 3 x 3 inner cores to carry out expansion operation, and storing after completion; adopting the image saved in the last step to perform expansion operation by using the 3 x 3 kernel again, and saving after completion; repeating the previous step until the color block on the picture is mostly changed to white. Images stored in the whole process are sequentially made into a video at the speed of one frame per second, and the video is shot by using a camera of an endoscope in a darkroom; determining a three-channel gain coefficient according to the three-channel mean value of each frame of image in the shot video and the color correction parameter of the camera of the endoscope, and processing each frame of image by adopting a gray world algorithm and the three-channel gain coefficient; dividing each processed frame image into color blocks, calculating the RGB color mean value of 3 x 3 range of the center of each color block in each frame image, numbering and recording; then converting the RGB color mean value within the range of 3 x 3 of the center of each color block into a Lab color space value, comparing the Lab color space value obtained by conversion with an international standard value, and calculating the chromaticity difference; and comparing the calculated chroma difference of each frame image with the acceptable maximum color difference, when the chroma difference of a certain frame image exceeds the acceptable maximum color difference, calculating the percentage of the pixel number of which the gray value is greater than or equal to the threshold value in the frame image, and taking the calculated percentage value as a preset ratio. Optionally, because the change curve of the color difference is similar to a step function, a curve may be drawn by using discrete color difference data, and a relatively suitable image is searched from the curve as a critical frame.
Preferably, the step S100 specifically includes steps S111 to S113:
and S111, copying the current frame image acquired by the camera of the endoscope in real time to obtain a copied image.
And S112, performing Gaussian smoothing processing on the copied image to obtain a processed copied image.
And S113, converting the processed copied image into a gray-scale image.
The method comprises the steps of copying a current frame image to obtain a copied image, performing Gaussian smoothing on the copied image, converting the processed copied image into a gray image, effectively eliminating noise in the image acquisition and transmission process, improving the image quality, reducing the influence on the image analysis and improving the image color correction quality.
Preferably, the step of acquiring the grayscale threshold in step S200 includes steps S211 to S215:
s211, carrying out image acquisition on the N-order gray-scale image through a camera of the endoscope to obtain a test gray-scale image; wherein N is a positive integer.
S212, obtaining the gray-scale value of each pixel in the test gray-scale image, and determining a reference gray-scale value according to the maximum gray-scale value and the preset percentage of the obtained gray-scale values of each pixel.
S213, uniformly dividing the test gray-scale image into N areas, and calculating the average gray-scale value of each area according to the gray-scale value of each pixel in the test gray-scale image.
S214, determining the smaller value and the larger value which are closest to the reference gray-scale value in the mean gray-scale value of each region.
S215, performing interpolation calculation according to the reference gray scale value, the smaller value and the larger value to obtain a gray scale corresponding to the reference gray scale value, and taking the gray scale corresponding to the reference gray scale value as the gray scale threshold value.
Taking N as an example 20, firstly, under normal light conditions, a camera of the endoscope performs image acquisition on a relatively fine 20-order rectangular grayscale image to obtain a test grayscale image. Then, obtaining gray-scale values of each pixel in the test gray-scale image, and multiplying the maximum gray-scale value in the obtained gray-scale values by a preset percentage to obtain a reference gray-scale value, wherein the preset percentage can be selected according to actual conditions without affecting the beneficial effects of the invention, and optionally, the preset percentage is 95%. Then, the test gray scale map is uniformly divided into 20 regions, and according to the obtained gray scale values of the pixels, the average value of the gray scale values of all the pixels in each region is calculated to be used as the average gray scale value of each region. And comparing the reference gray-scale value with the average gray-scale value of each region, determining the value which is closest to the reference gray-scale value and smaller than the reference gray-scale value in the average gray-scale values of all the regions as a smaller value, and determining the value which is closest to the reference gray-scale value and larger than the reference gray-scale value in the average gray-scale values of all the regions as a larger value. And finally, calculating to obtain the gray scale corresponding to the reference gray scale value by using an interpolation method according to the reference gray scale value, the smaller value and the larger value, and taking the gray scale corresponding to the reference gray scale value as a gray threshold value. Preferably, after the gray scale corresponding to the reference gray scale value is obtained, the gray scale corresponding to the reference gray scale value is rounded to be used as the gray threshold.
As a preferred scheme, the preset white balance adjustment algorithm in the step S300 is a gray world algorithm;
referring to fig. 2, the performing white balance processing on the current frame image by using a preset white balance adjustment algorithm to obtain the color-corrected current frame image specifically includes steps S311 to S312:
s311, determining a current gray level mean value parameter of a gray level world algorithm according to the gray level mean value of the first type of pixels.
It should be noted that, after determining the current gray level mean value parameter of the gray level world algorithm according to the gray level mean value of the first-class pixel, the current gray level mean value parameter of the frame image needs to be recorded.
Further, the method for determining the current gray level mean parameter of the gray world algorithm according to the gray level mean of the first-class pixel in the step S311 specifically includes steps S3111 to S3112:
s3111, calculating a gray level mean value of the first type of pixels.
And calculating the average value of the gray values of all the pixels in the first type of pixels to serve as the gray average value of the first type of pixels.
S3112, trying to obtain a historical gray level mean value parameter; the historical gray level mean value parameter is a gray level mean value parameter adopted when a gray level world algorithm is adopted to perform white balance processing on a previous frame of image; if the historical gray level mean value parameter can be obtained, determining the current gray level mean value parameter according to the gray level mean value of the first type of pixels and the historical gray level mean value parameter; and if the historical gray level mean value parameter cannot be acquired, determining a current gray level mean value parameter of a gray level world algorithm according to the gray level mean value of the first type of pixels.
Specifically, since the images acquired by the camera of the endoscope are continuous, and the gray level average parameter between two continuous frames of images with higher brightness is associated to a certain extent, a better effect can be obtained by performing color correction according to the gray level average parameter of the two continuous frames of images, when trying to obtain the gray level average parameter when performing white balance processing on the previous frame of image by using a gray level world algorithm, if the historical gray level average parameter can be obtained, the previous frame of image is a bright tone image, and at this time, the current gray level average parameter is determined according to the calculated gray level average of the first type of pixels and the historical gray level average parameter, optionally, the gray level average of the first type of pixels is divided by 2, multiplied by the historical gray level average parameter, and then rounded, so as to serve as the current gray level average parameter. If the historical gray level mean value parameter cannot be acquired, it is indicated that the previous frame of image is a dark tone image or the current frame of image is a first frame of image acquired by a camera of the endoscope, and at this time, the current gray level mean value parameter of the gray level world algorithm is determined according to the gray level mean value of the first type of pixels, optionally, the gray level mean value of the first type of pixels is divided by 2 and is rounded to serve as the gray level mean value parameter.
And S312, performing white balance processing on the current frame image by adopting a gray world algorithm and the current gray mean parameter to obtain the current frame image after color correction.
After the current gray mean parameter is obtained, white balance processing is carried out on the current frame image by adopting a gray world algorithm and the current gray mean parameter so as to carry out color correction on the current frame image, and thus the current frame image after color correction is obtained.
Preferably, the color correction parameters in step S300 include a red component weighting coefficient, a green component weighting coefficient, and a blue component weighting coefficient;
referring to fig. 3, the correcting the color of the current frame image according to the color correction parameter of the camera of the endoscope to obtain the color-corrected current frame image specifically includes steps S321 to S323:
s321, acquiring three-channel components of the current frame image; wherein the three channel components include a red component, a green component, and a blue component.
The red, green and blue components of the current frame image are calculated as three channel components of the current frame image.
And S322, multiplying the three-channel components by the weighting coefficients in the color correction parameters corresponding to the three-channel components respectively to obtain the three-channel components suitable for the camera.
And respectively multiplying the red component, the green component and the blue component of the current frame image by a red component weighting coefficient, a green component weighting coefficient and a blue component weighting coefficient in the color correction parameters of the camera of the endoscope to obtain three channel components adaptive to the camera.
And S323, combining the three-channel components of the adaptive camera to obtain the current frame image after color correction.
And combining the three-channel components adapting to the camera to obtain the current frame image after color correction so as to realize color correction of the current frame image.
Further, the step of obtaining the color correction parameter specifically includes steps S1 to S8:
s1, acquiring images of the international standard color card through the camera of the endoscope to obtain a test color card image; the international standard color card comprises M color blocks, and M is a positive integer.
Taking M as an example, in a darkroom environment with normal illumination, the 24 color international standard color chart is subjected to image acquisition by using a camera of an endoscope with a normal focal length, and the acquired 24 color international standard color chart is taken as a test color chart, and then the process proceeds to step S2.
And S2, calculating a red component gain coefficient, a green component gain coefficient and a blue component gain coefficient of the test color chart by adopting a gray world algorithm according to the RGB values of all pixels in the test color chart, and respectively setting the corresponding weighted values to be 1.
Calculating the mean value of the RGB values of all pixels in the test color card chart, taking the calculated mean value as a gray mean value parameter of a gray world algorithm, calculating a red component gain coefficient, a green component gain coefficient and a blue component gain coefficient of the test color card chart by using the gray world algorithm, setting the corresponding weighted values to 1, and then entering step S3.
S3, adjusting the color value of the test color chart according to the red component gain coefficient, the green component gain coefficient, the blue component gain coefficient and the corresponding weighted value of the red component gain coefficient, the green component gain coefficient and the blue component gain coefficient of the test color chart to obtain the adjusted test color chart.
Multiplying the red component gain coefficient, the green component gain coefficient and the blue component gain coefficient of the test color card chart with the corresponding weighted values respectively to serve as gain coefficients of a gray world algorithm, adjusting the color value of the test color card chart by the gray world algorithm to obtain the adjusted test color card chart, and then entering step S4.
And S4, calculating the Lab color space value of each color block in the adjusted test color chart.
Specifically, the RGB mean value of the pixels in the range of 3 × 3 from the center of each color block in the adjusted test chart is calculated, and the RGB mean value of the pixels in the range of 3 × 3 from the center of each color block is converted into a Lab color space value to serve as the Lab color space value of each color block, and then the procedure goes to step S5.
S5, determining the chromaticity difference between the adjusted test color card chart and the international standard color card according to the Lab color space value of each color block and the international standard Lab color space value corresponding to the color block; wherein the chromaticity differences include red-green chromaticity difference and yellow-blue chromaticity difference.
It will be appreciated that each color patch has its corresponding international standard Lab color space value. And calculating the red-green chromaticity difference and the yellow-blue chromaticity difference between the adjusted test color chart and the international standard color chart according to the Lab color space value of each color block and the international standard Lab color space value corresponding to the color block to determine the chromaticity difference between the adjusted test color chart and the international standard color chart, and then entering the step S6. And determining that the color display effect of the image is red, green, yellow or blue through the chromaticity difference between the adjusted test color card graph and the international standard color card.
And S6, judging whether the chromaticity differences are all larger than a preset chromaticity difference threshold value, if so, executing a step S7, and if not, executing a step S8.
After the chromaticity difference is determined, comparing the chromaticity difference with a preset chromaticity difference threshold value, thereby judging whether the chromaticity difference of red and green and the chromaticity difference of yellow and blue are both larger than the preset chromaticity difference threshold value, if so, executing step S7 to continue to perform color correction on the test color chart, if not, determining that the chromaticity difference meets the convergence requirement, and executing step S8. It can be understood that, in specific implementation, the preset chroma difference threshold may be selected according to actual situations, without affecting the beneficial effects of the present invention, and optionally, the preset chroma difference threshold is 5.
S7, modifying the weighted value of the red component gain coefficient or/and the weighted value of the blue component gain coefficient in the step S3 according to the chromaticity difference, and returning to the step S3.
And if the chromaticity difference of the red, the green or the yellow is larger than a preset chromaticity difference threshold value, modifying the weighted value of the gain coefficient of the red component or/and the weighted value of the gain coefficient of the blue component in the step S3 correspondingly according to the chromaticity situation of the image, and returning to the step S3 to continuously execute the process to carry out color correction on the test color chart. Preferably, the weighted value of the red component gain coefficient or/and the weighted value of the blue component gain coefficient in step S3 above may be step-corrected by using a step value, and optionally, the step value may be 0.001.
It should be noted that, in step S3, decreasing the weighting value of the red component gain coefficient effectively decreases the red-biased image, decreasing the weighting value of the blue component gain coefficient effectively decreases the blue-biased image, increasing the weighting value of the red component gain coefficient effectively decreases the green-biased image, and increasing the weighting value of the blue component gain coefficient effectively decreases the yellow-biased image. For example, if it is detected that the image color display effect is red and blue, the step value of 0.001 is used to modify both the weighted value of the red component gain coefficient and the weighted value of the blue component gain coefficient in step S3 to 0.999, and the process returns to step S3, and repeats steps S3 to S6, where if the difference between the chromaticity of yellow and blue is within the preset chromaticity difference threshold and the difference between the chromaticity of red and green is still greater than the preset chromaticity difference threshold, indicating that the color of blue converges, but the display effect is still red, the step S3 is modified again to modify the weighted value of the red component gain coefficient to 0.999 × 0.999, and steps S3 to S6 are repeated.
S8, using the weighted value of the red component gain coefficient, the weighted value of the green component gain coefficient and the weighted value of the blue component gain coefficient in the step S3 as the red component weighting coefficient, the green component weighting coefficient and the blue component weighting coefficient in the color correction parameter, respectively.
If the chromaticity difference between red and green and the chromaticity difference between yellow and blue are within the preset chromaticity difference threshold, indicating that the chromaticity difference meets the convergence requirement, and respectively taking the weighted value of the gain coefficient of the red component, the weighted value of the gain coefficient of the green component and the weighted value of the gain coefficient of the blue component at the moment in the step S3 as the weighted coefficient of the red component, the weighted coefficient of the green component and the weighted coefficient of the blue component in the color correction parameter, so as to be used for subsequently correcting the color of the current frame image.
It will be appreciated that any combination of the above preferences may be used to arrive at a more preferred embodiment.
The image color correction method suitable for the endoscope provided by the embodiment of the invention comprises the following steps of firstly, acquiring a gray-scale image of a current frame image acquired by a camera of the endoscope in real time; calculating the ratio of the first type of pixels in the gray-scale image; the first type of pixels are pixels with gray values larger than or equal to a gray threshold value; then, judging whether the ratio is greater than or equal to a preset ratio or not; if so, performing white balance processing on the current frame image by adopting a preset white balance adjustment algorithm to obtain a current frame image after color correction; if not, correcting the color of the current frame image according to the color correction parameter of the camera of the endoscope to obtain the current frame image after color correction, thereby realizing color correction on the image acquired by the endoscope in real time. According to the embodiment of the invention, the ratio of the pixels with the gray value larger than or equal to the gray threshold value in the current frame image collected by the camera of the endoscope is compared with the preset ratio, so that whether the current frame image is a light-tone image or a dark-tone image is determined, and therefore, the white balance processing can be correspondingly carried out on the current frame image by adopting the preset white balance adjusting algorithm according to the tone of the current frame image, or the color of the current frame image is corrected according to the color correction parameter of the camera of the endoscope, so that the color correction of the image collected by the endoscope is realized in real time, the color of the image approaches to the real color, and the color cast of the image can be accurately reduced.
The embodiment of the invention also provides an image color correction device suitable for an endoscope, which can implement all the procedures of the image color correction method suitable for the endoscope.
Fig. 4 is a schematic structural diagram of an embodiment of the image color correction device suitable for an endoscope according to the present invention.
The embodiment of the invention provides an image color correction device suitable for an endoscope, which comprises:
the acquisition module 21 is configured to acquire a gray scale image of a current frame image acquired by a camera of the endoscope in real time;
the calculation module 22 is used for calculating the ratio of the first type of pixels in the gray scale map; the first type of pixels are pixels with gray values larger than or equal to a gray threshold value;
the correcting module 23 is configured to determine whether the ratio is greater than or equal to a preset ratio, if so, perform white balance processing on the current frame image by using a preset white balance adjustment algorithm to obtain a color-corrected current frame image, and if not, correct the color of the current frame image according to the color correction parameter of the camera of the endoscope to obtain the color-corrected current frame image.
The image color correction device suitable for the endoscope provided by the embodiment of the invention comprises the following steps of firstly, acquiring a gray-scale image of a current frame image acquired by a camera of the endoscope in real time; calculating the ratio of the first type of pixels in the gray-scale image; the first type of pixels are pixels with gray values larger than or equal to a gray threshold value; then, judging whether the ratio is greater than or equal to a preset ratio or not; if so, performing white balance processing on the current frame image by adopting a preset white balance adjustment algorithm to obtain a current frame image after color correction; if not, correcting the color of the current frame image according to the color correction parameter of the camera of the endoscope to obtain the current frame image after color correction, thereby realizing color correction on the image acquired by the endoscope in real time. According to the embodiment of the invention, the ratio of the pixels with the gray value larger than or equal to the gray threshold value in the current frame image collected by the camera of the endoscope is compared with the preset ratio, so that whether the current frame image is a light-tone image or a dark-tone image is determined, and therefore, the white balance processing can be correspondingly carried out on the current frame image by adopting the preset white balance adjusting algorithm according to the tone of the current frame image, or the color of the current frame image is corrected according to the color correction parameter of the camera of the endoscope, so that the color correction of the image collected by the endoscope is realized in real time, the color of the image approaches to the real color, and the color cast of the image can be accurately reduced.
Fig. 5 is a schematic structural diagram of another embodiment of the image color correction device suitable for an endoscope according to the present invention.
An image color correction device suitable for an endoscope provided by an embodiment of the present invention includes a processor 31, a memory 32, and a computer program stored in the memory and configured to be executed by the processor 31, wherein the processor 31 implements the image color correction method suitable for an endoscope according to any one of the above embodiments when executing the computer program.
In addition, the embodiment of the present invention further provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program runs, the apparatus where the computer-readable storage medium is located is controlled to execute the image color correction method suitable for an endoscope according to any one of the above embodiments.
The processor 31, when executing the computer program, implements the steps in the various embodiments of the endoscope-appropriate image color correction method described above, such as all of the steps of the endoscope-appropriate image color correction method shown in fig. 1. Alternatively, the processor 31 may implement the functions of the modules/units in the embodiments of the image color correction apparatus for endoscope described above, for example, the functions of the modules of the image color correction apparatus for endoscope shown in fig. 4, when executing the computer program.
Illustratively, the computer program may be divided into one or more modules, which are stored in the memory 32 and executed by the processor 31 to accomplish the present invention. The one or more modules may be a series of computer program instruction segments capable of performing specific functions for describing the execution of the computer program in the endoscope-compatible image color correction apparatus. For example, the computer program may be divided into an acquisition module, a calculation module and a correction module, each module having the following specific functions: the acquisition module is used for acquiring a gray scale image of a current frame image acquired by a camera of the endoscope in real time; the calculation module is used for calculating the ratio of the first type of pixels in the gray scale image; the first type of pixels are pixels with gray values larger than or equal to a gray threshold value; and the correction module is used for judging whether the ratio is greater than or equal to a preset ratio or not, if so, performing white balance processing on the current frame image by adopting a preset white balance adjustment algorithm to obtain the current frame image after color correction, and if not, correcting the color of the current frame image according to the color correction parameter of the camera of the endoscope to obtain the current frame image after color correction.
The image color correction device suitable for the endoscope can be a desktop computer, a notebook computer, a palm computer, a cloud server and other computing equipment. The image color correction device suitable for the endoscope can include, but is not limited to, a processor 31 and a memory 32. It will be understood by those skilled in the art that the schematic diagram is merely an example of an image color correction apparatus suitable for an endoscope, and does not constitute a limitation of the image color correction apparatus suitable for an endoscope, and may include more or less components than those shown, or combine some components, or different components, for example, the image color correction apparatus suitable for an endoscope may further include an input-output device, a network access device, a bus, and the like.
The Processor 31 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc., and the processor 31 is a control center of the endoscope-compatible image color correction apparatus, and various interfaces and lines are used to connect various parts of the entire endoscope-compatible image color correction apparatus.
The memory 32 can be used for storing the computer program and/or the module, and the processor 31 can realize various functions of the image color correction apparatus suitable for the endoscope by running or executing the computer program and/or the module stored in the memory 32 and calling the data stored in the memory 32. The memory 32 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
Wherein, the module/unit integrated with the image color correction device for endoscope can be stored in a computer readable storage medium if it is implemented in the form of software functional unit and sold or used as a stand-alone product. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like.
It should be noted that the above-described device embodiments are merely illustrative, where the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. In addition, in the drawings of the embodiment of the apparatus provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, and may be specifically implemented as one or more communication buses or signal lines. One of ordinary skill in the art can understand and implement it without inventive effort.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (9)
1. An image color correction method suitable for an endoscope, comprising:
acquiring a gray scale image of a current frame image acquired by a camera of an endoscope in real time;
calculating the ratio of the first type of pixels in the gray-scale image; the first type of pixels are pixels with gray values larger than or equal to a gray threshold value;
judging whether the ratio is greater than or equal to a preset ratio or not, if so, performing white balance processing on the current frame image by adopting a preset white balance adjustment algorithm to obtain a current frame image after color correction, and if not, correcting the color of the current frame image according to color correction parameters of a camera of the endoscope to obtain the current frame image after color correction; wherein the color correction parameters comprise a red component weighting coefficient, a green component weighting coefficient, and a blue component weighting coefficient;
the step of obtaining the color correction parameter specifically includes:
s1, acquiring images of the international standard color card through the camera of the endoscope to obtain a test color card image; the international standard color card comprises M color blocks, wherein M is a positive integer;
s2, calculating a red component gain coefficient, a green component gain coefficient and a blue component gain coefficient of the test color chart by adopting a gray world algorithm according to the RGB values of all pixels in the test color chart, and respectively setting the corresponding weighted values to be 1;
s3, adjusting the color value of the test color chart according to the red component gain coefficient, the green component gain coefficient, the blue component gain coefficient and the corresponding weighted value of the red component gain coefficient, the green component gain coefficient and the blue component gain coefficient of the test color chart to obtain the adjusted test color chart;
s4, calculating the Lab color space value of each color block in the adjusted test color chart;
s5, determining the chromaticity difference between the adjusted test color card chart and the international standard color card according to the Lab color space value of each color block and the international standard Lab color space value corresponding to the color block; wherein the chromaticity differences comprise a red-green chromaticity difference and a yellow-blue chromaticity difference;
s6, judging whether the chromaticity differences are all larger than a preset chromaticity difference threshold value, if so, executing a step S7, and if not, executing a step S8;
s7, modifying the weighted value of the gain coefficient of the red component or/and the weighted value of the gain coefficient of the blue component in the step S3 according to the chromaticity difference, and returning to the step S3;
s8, using the weighted value of the red component gain coefficient, the weighted value of the green component gain coefficient and the weighted value of the blue component gain coefficient in the step S3 as the red component weighting coefficient, the green component weighting coefficient and the blue component weighting coefficient in the color correction parameter, respectively.
2. The image color correction method suitable for an endoscope according to claim 1, wherein the acquiring a gray scale map of a current frame image acquired by a camera of the endoscope in real time specifically comprises:
copying a current frame image acquired by a camera of an endoscope in real time to obtain a copied image;
performing Gaussian smoothing processing on the copied image to obtain a processed copied image;
and converting the processed copy image into a gray-scale image.
3. The image color correction method suitable for an endoscope according to claim 1 or 2, wherein the step of obtaining the gray threshold specifically includes:
acquiring an image of the N-order gray-scale image through a camera of the endoscope to obtain a test gray-scale image; wherein N is a positive integer;
acquiring the gray-scale value of each pixel in the test gray-scale image, and determining a reference gray-scale value according to the maximum gray-scale value and a preset percentage of the acquired gray-scale values of each pixel;
uniformly dividing the test gray-scale image into N areas, and calculating the average gray-scale value of each area according to the gray-scale value of each pixel in the test gray-scale image;
determining the smaller value and the larger value which are closest to the reference gray-scale value in the mean gray-scale value of each area;
and carrying out interpolation calculation according to the reference gray scale value, the smaller value and the larger value to obtain a gray scale corresponding to the reference gray scale value, and taking the gray scale corresponding to the reference gray scale value as the gray threshold value.
4. The image color correction method for an endoscope, according to claim 1, wherein said preset white balance adjustment algorithm is a gray world algorithm;
performing white balance processing on the current frame image by using a preset white balance adjustment algorithm to obtain a color-corrected current frame image, specifically including:
determining a current gray level mean value parameter of a gray level world algorithm according to the gray level mean value of the first type of pixels;
and carrying out white balance processing on the current frame image by adopting a gray world algorithm and the current gray mean value parameter to obtain the current frame image after color correction.
5. The image color correction method suitable for an endoscope according to claim 4, wherein said determining a current gray level mean parameter of a gray level world algorithm according to the gray level mean of the first type of pixels specifically comprises:
calculating the gray average value of the first type of pixels;
trying to obtain a historical gray level mean parameter; the historical gray level mean value parameter is a gray level mean value parameter adopted when a gray level world algorithm is adopted to perform white balance processing on a previous frame of image;
if the historical gray level mean value parameter can be obtained, determining the current gray level mean value parameter according to the gray level mean value of the first type of pixels and the historical gray level mean value parameter;
and if the historical gray level mean value parameter cannot be acquired, determining a current gray level mean value parameter of a gray level world algorithm according to the gray level mean value of the first type of pixels.
6. The image color correction method applicable to an endoscope according to claim 1,
the correcting the color of the current frame image according to the color correction parameter of the camera of the endoscope to obtain the current frame image after color correction specifically comprises:
acquiring three-channel components of the current frame image; wherein the three channel components include a red component, a green component, and a blue component;
multiplying the three-channel components by the weighting coefficients in the color correction parameters corresponding to the three-channel components respectively to obtain three-channel components adaptive to the camera;
and combining the three-channel components of the adaptive camera to obtain the current frame image after color correction.
7. An image color correction apparatus adapted for use with an endoscope, comprising:
the acquisition module is used for acquiring a gray scale image of a current frame image acquired by a camera of the endoscope in real time;
the calculation module is used for calculating the ratio of the first type of pixels in the gray scale image; the first type of pixels are pixels with gray values larger than or equal to a gray threshold value;
the correction module is used for judging whether the ratio is larger than or equal to a preset ratio or not, if so, performing white balance processing on the current frame image by adopting a preset white balance adjustment algorithm to obtain a current frame image after color correction, and if not, correcting the color of the current frame image according to the color correction parameter of the camera of the endoscope to obtain the current frame image after color correction; wherein the color correction parameters comprise a red component weighting coefficient, a green component weighting coefficient, and a blue component weighting coefficient;
the step of obtaining the color correction parameter specifically includes:
s1, acquiring images of the international standard color card through the camera of the endoscope to obtain a test color card image; the international standard color card comprises M color blocks, wherein M is a positive integer;
s2, calculating a red component gain coefficient, a green component gain coefficient and a blue component gain coefficient of the test color chart by adopting a gray world algorithm according to the RGB values of all pixels in the test color chart, and respectively setting the corresponding weighted values to be 1;
s3, adjusting the color value of the test color chart according to the red component gain coefficient, the green component gain coefficient, the blue component gain coefficient and the corresponding weighted value of the red component gain coefficient, the green component gain coefficient and the blue component gain coefficient of the test color chart to obtain the adjusted test color chart;
s4, calculating the Lab color space value of each color block in the adjusted test color chart;
s5, determining the chromaticity difference between the adjusted test color card chart and the international standard color card according to the Lab color space value of each color block and the international standard Lab color space value corresponding to the color block; wherein the chromaticity differences comprise a red-green chromaticity difference and a yellow-blue chromaticity difference;
s6, judging whether the chromaticity differences are all larger than a preset chromaticity difference threshold value, if so, executing a step S7, and if not, executing a step S8;
s7, modifying the weighted value of the gain coefficient of the red component or/and the weighted value of the gain coefficient of the blue component in the step S3 according to the chromaticity difference, and returning to the step S3;
s8, using the weighted value of the red component gain coefficient, the weighted value of the green component gain coefficient and the weighted value of the blue component gain coefficient in the step S3 as the red component weighting coefficient, the green component weighting coefficient and the blue component weighting coefficient in the color correction parameter, respectively.
8. An image color correction apparatus adapted for an endoscope, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the processor implementing the image color correction method adapted for an endoscope according to any one of claims 1 to 6 when executing the computer program.
9. A computer-readable storage medium, comprising a stored computer program, wherein the computer program, when executed, controls an apparatus in which the computer-readable storage medium is located to perform the image color correction method for an endoscope according to any one of claims 1 to 6.
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Families Citing this family (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110505459B (en) * | 2019-08-16 | 2020-12-11 | 域鑫科技（惠州）有限公司 | Image color correction method, device and storage medium suitable for endoscope |
| CN111144421B (en) * | 2019-12-10 | 2024-02-13 | 深圳市优必选科技股份有限公司 | Object color recognition method and device and throwing equipment |
| CN113129356B (en) * | 2020-01-16 | 2022-08-23 | 安翰科技(武汉)股份有限公司 | Capsule endoscope system, image staining area recognition method thereof, and storage medium |
| CN111726600A (en) * | 2020-06-30 | 2020-09-29 | 深圳市精锋医疗科技有限公司 | Image processing method, device and storage medium for stereoscopic endoscope |
| CN112277274B (en) * | 2020-11-05 | 2022-11-11 | 宁波科德新能源科技有限公司 | Integrated color matching method and system for plastic part, storage medium and injection molding equipment |
| CN113157221B (en) * | 2021-03-18 | 2022-11-18 | 厦门汉印电子技术有限公司 | Parameter calibration method, device, equipment and storage medium for visible card printer |
| CN114025088B (en) * | 2021-10-31 | 2023-08-22 | 中汽院(重庆)汽车检测有限公司 | Method for realizing safety monitoring of all-round image by arranging intelligent camera on operating automobile |
| CN114283731B (en) * | 2021-12-30 | 2023-09-22 | 昆山国显光电有限公司 | Pressure drop compensation method, apparatus, device, medium and program product |
| CN114374830B (en) * | 2022-01-06 | 2024-03-08 | 杭州海康威视数字技术股份有限公司 | Image white balance method, electronic device and computer readable storage medium |
| CN114298956B (en) * | 2022-03-09 | 2022-06-28 | 广东欧谱曼迪科技有限公司 | Image fusion method of dual-fluorescence endoscope, electronic equipment and device |
| CN114679524B (en) * | 2022-03-23 | 2023-06-16 | 西安邮电大学 | Rapid method for rapidly detecting and repairing high-energy visible light under endoscope |
| CN115174876B (en) * | 2022-04-12 | 2023-08-11 | 北京印刷学院 | Color code design and manufacturing method for medical endoscope imaging color analysis and correction |
| CN115131251B (en) * | 2022-08-30 | 2022-12-27 | 之江实验室 | Image color cast correction method, device and storage medium |
| CN115311317A (en) * | 2022-10-12 | 2022-11-08 | 广州中平智能科技有限公司 | Laparoscope image segmentation method and system based on ScaleFormer algorithm |
| CN115759517A (en) * | 2022-11-23 | 2023-03-07 | 杭州柏源科技有限公司 | Hotel check-in system based on biological recognition |
| CN115797344B (en) * | 2023-02-06 | 2023-04-21 | 智联信通科技股份有限公司 | Machine room equipment identification management method based on image enhancement |
| CN116310448B (en) * | 2023-05-24 | 2023-08-04 | 山东曙岳车辆有限公司 | Container assembly matching detection method based on computer vision |
| CN116703798B (en) * | 2023-08-08 | 2023-10-13 | 西南科技大学 | Esophagus multi-mode endoscope image enhancement fusion method based on self-adaptive interference suppression |
| CN116993624B (en) * | 2023-09-25 | 2023-12-29 | 湖南肆玖科技有限公司 | Image data processing method, device and medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2003085963A1 (en) * | 2002-04-02 | 2003-10-16 | Freescale Semiconductor, Inc. | Digital color image pre-processing |
| CN105049680A (en) * | 2014-04-25 | 2015-11-11 | 佳能株式会社 | Image processing apparatus that performs image restoration processing and image processing method |
| CN108289590A (en) * | 2015-11-17 | 2018-07-17 | 奥林巴斯株式会社 | Endoscopic system, image processing apparatus, image processing method and program |
Family Cites Families (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP4504339B2 (en) * | 2006-09-22 | 2010-07-14 | オリンパスメディカルシステムズ株式会社 | Endoscope device |
| WO2011162111A1 (en) * | 2010-06-25 | 2011-12-29 | オリンパスメディカルシステムズ株式会社 | Endoscope device |
| CN103037224A (en) * | 2012-12-07 | 2013-04-10 | 珠海全志科技股份有限公司 | Image white balance processing method and device |
| CN103491357B (en) * | 2013-10-14 | 2016-04-13 | 旗瀚科技股份有限公司 | A kind of auto white balance treatment method of image sensor |
| WO2015194422A1 (en) * | 2014-06-17 | 2015-12-23 | オリンパス株式会社 | Endoscope system and white balance adjustment method for same |
| JP6099603B2 (en) * | 2014-08-04 | 2017-03-22 | 富士フイルム株式会社 | MEDICAL IMAGE PROCESSING DEVICE, ITS OPERATION METHOD, AND ENDOSCOPE SYSTEM |
| CN104469334B (en) * | 2014-12-10 | 2016-08-17 | 深圳市理邦精密仪器股份有限公司 | A kind of Medical Devices obtain the processing method and processing device of view data |
| CN105046260B (en) * | 2015-07-31 | 2019-01-04 | 小米科技有限责任公司 | Image pre-processing method and device |
| JP2018038460A (en) * | 2016-09-05 | 2018-03-15 | Hoya株式会社 | Color adjustment tool and electronic endoscope system |
| CN108063926B (en) * | 2017-12-25 | 2020-01-10 | Oppo广东移动通信有限公司 | Image processing method and device, computer readable storage medium and computer device |
| CN108063934B (en) * | 2017-12-25 | 2020-01-10 | Oppo广东移动通信有限公司 | Image processing method and device, computer readable storage medium and computer device |
| CN107920242B (en) * | 2017-12-28 | 2019-08-16 | 努比亚技术有限公司 | A kind of optimization method of automatic white balance, terminal and computer readable storage medium |
| CN108230412B (en) * | 2018-01-19 | 2022-02-18 | 浙江大华技术股份有限公司 | Infrared image compression method and device |
| CN110505459B (en) * | 2019-08-16 | 2020-12-11 | 域鑫科技（惠州）有限公司 | Image color correction method, device and storage medium suitable for endoscope |
-
2019
- 2019-08-16 CN CN201910760188.2A patent/CN110505459B/en active Active
- 2019-12-05 WO PCT/CN2019/123436 patent/WO2021031458A1/en active Application Filing
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2003085963A1 (en) * | 2002-04-02 | 2003-10-16 | Freescale Semiconductor, Inc. | Digital color image pre-processing |
| CN105049680A (en) * | 2014-04-25 | 2015-11-11 | 佳能株式会社 | Image processing apparatus that performs image restoration processing and image processing method |
| CN108289590A (en) * | 2015-11-17 | 2018-07-17 | 奥林巴斯株式会社 | Endoscopic system, image processing apparatus, image processing method and program |
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| CN110505459A (en) | 2019-11-26 |
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Denomination of invention: Image color correction method, device and storage medium for endoscope Effective date of registration: 20220331 Granted publication date: 20201211 Pledgee: Agricultural Bank of China Limited Huizhou Dayawan sub branch Pledgor: YUXIN TECHNOLOGY (HUIZHOU) Co.,Ltd. Registration number: Y2022980003663 |