A computer-based image processing denoising device

Abstract

The application discloses a computer-based image processing denoising device. The application comprises a central control system, which is bidirectionally connected with an image acquisition module through wireless connection, the output end of the image acquisition module is electrically connected with the input end of an image analysis unit, the central control system is bidirectionally connected with a model construction unit through wireless connection, and the output end of the model construction unit is electrically connected with the input end of a denoising module. The application relates to the technical field of image processing. The computer-based image processing denoising device regards an image as a two-dimensional matrix, generates a coordinate position, directly obtains a pixel value corresponding to the coordinate position, then calculates the weighted sum of the difference values of each direction pixel and the center point pixel value in four directions for each pixel point, thereby avoiding the judgment of edges or flat areas as noise, improving the judgment accuracy of noise points, and making the image not easy to blur after denoising.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of image processing, in particular to a computer-based image processing denoising device. BACKGROUND

[0002] The technology of image processing with computer is to analyze image to achieve the desired results, also known as image processing, image processing generally refers to digital image processing, digital image refers to a large two-dimensional array obtained by shooting with industrial camera, video camera, scanner and other devices, the element of the array is called pixel, and the value is called gray value, image processing technology generally includes image compression, enhancement and restoration, matching, description and identification three parts, the purpose of image processing includes improving the visual quality of image, extracting some features or special information contained in the image, these extracted features or information often provide convenience for computer analysis of image, image data transformation, coding and compression to facilitate image storage and transmission, no matter what purpose of image processing, image processing system composed of computer and image special equipment is needed to input, process and output image data.

[0003] At present, mean filter as a common and fastest image denoising method mainly adopts field average method, which refers to giving a template to the target pixel on the image, the template includes the surrounding adjacent pixels, and the average value of all pixels in the template is used to replace the original pixel value, but this method seriously damages the edge of the image and blurs the image in the use process, affecting the quality of the final imaging. SUMMARY

[0004] The present application aims at the deficiencies of the prior art, and provides a computer-based image processing denoising device, which solves the problem that the mean filter as a common image denoising method seriously damages the edge of the image and blurs the image in the use process, affecting the quality of the final imaging.

[0005] To achieve the above object, the present application is realized by the following technical scheme:

[0006] The application discloses a computer-based image processing denoising device, which comprises a central control system, wherein the central control system is bidirectionally connected with an image acquisition module through wireless connection, the output end of the image acquisition module is electrically connected with the input end of an image analysis unit, the central control system is bidirectionally connected with a model construction unit through wireless connection, the output end of the model construction unit is electrically connected with the input end of a denoising module, the central control system is bidirectionally connected with a comparison module through wireless connection, the central control system is bidirectionally connected with a database through wireless connection, the central control system is bidirectionally connected with a man-machine interaction unit through wireless connection, the central control system is bidirectionally connected with a wireless transmission module through wireless connection, and the wireless transmission module is bidirectionally connected with a display module through wireless connection.

[0007] Preferably, the output end of the image analysis unit is electrically connected with the input end of the central control system, and the denoising module is bidirectionally connected with the central control system through wireless connection.

[0008] Preferably, the image analysis unit comprises a conversion module, a coordinate generation module, a scanning module and a region division module.

[0009] Preferably, the model construction unit comprises a formula generation module, a substitution module, a calculation module and a noise point judgment module.

[0010] Preferably, the man-machine interaction unit comprises a face recognition module, a login module and a touch interaction module.

[0011] Preferably, the database comprises a storage module, the storage module is bidirectionally connected with a classification module through wireless connection, and the storage module is bidirectionally connected with a deletion module through wireless connection.

[0012] Preferably, the input end of the storage module is electrically connected with the output end of a receiving module, and the storage module is bidirectionally connected with a protection module through wireless connection.

[0013] The application further discloses a computer-based image processing denoising method, which specifically comprises the following steps.

[0014] S1, the image acquisition module is used for acquiring a digital image and uploading the digital image to an image analysis unit; a conversion module is used for converting the digital image into two-dimensional image information; a scanning module is used for globally and locally scanning the features of the two-dimensional image; the image is regarded as a two-dimensional matrix; a coordinate generation module generates a coordinate position and directly obtains a pixel value corresponding to the coordinate position; and a region division module is used for dividing the matrix into a window with a size of 5*5.

[0015] S2, the formula generation module in the model construction unit is used for generating a weighted formula, the substitution module is used for substituting relevant values of the formula, and the calculation module is used for calculating the formula, the difference weighted sum of each direction pixel and the center point pixel value in four directions is calculated for each pixel point, after the weighted sum on the four lines is calculated, when the minimum value of the four weighted sums is also greater than the threshold value, the threshold value needs to be adjusted by oneself, it is indicated that the difference of each direction with the center point is relatively large, the noise judgment module judges that it is noise, otherwise, it is an edge or a flat area;

[0016] S3, after the judgment is completed, the denoising module is used for denoising the image according to the result of the noise judgment module, the denoised image and the original image are transmitted to the database, the receiving module is used for receiving image information, the storage module is used for saving the denoised image and the original image, the classification module saves the denoised image and the original image separately, and the deletion module is used for deleting the expired image in the storage module;

[0017] S4, meanwhile, the denoised image is uploaded to the central control system, the comparison module is used for comparing the denoised image with the original image, the wireless transmission module is used for uploading the denoised image to the display module, and the display module is used for displaying the denoised image;

[0018] S5, a user performs face recognition through the face recognition module, after successful recognition, the login module is used for user login, and the touch interaction module is used for user instruction control on the display screen.

[0019] The application has the following beneficial effects:

[0020] (1), the image processing denoising device based on the computer, by regarding the image as a two-dimensional matrix, generating a coordinate position, directly obtaining a pixel value corresponding to the coordinate position, then calculating the difference weighted sum of each direction pixel and the center point pixel value in four directions for each pixel point, so that the edge or flat area is avoided to be determined as noise, the judgment accuracy of the noise point is improved, and the image is not easy to blur after denoising.

[0021] (2), the image processing denoising device based on the computer, when the image is analyzed, the scanning module globally and locally scans the features of the two-dimensional image, and the omnibearing scanning makes the image recognition more accurate, and provides a good foundation for subsequent noise point judgment.

[0022] (3), the computer-based image processing denoising device, through the database includes storage module, storage module is connected with classification module through wireless two-way, the input end of storage module and the output end of receiving module are electrically connected, storage module is connected with protection module through wireless two-way, the image after denoising and original image are stored in database, and it is classified, so as to facilitate subsequent extraction traceability. BRIEF DESCRIPTION OF DRAWINGS

[0023] Figure 1 It is the structural principle diagram of the system of the application;

[0024] Figure 2 It is the structural principle diagram of the image analysis unit of the application;

[0025] Figure 3 It is the structural principle diagram of the model construction unit of the application;

[0026] Figure 4 It is the structural principle diagram of the man-machine interaction unit of the application;

[0027] Figure 5 It is the structural principle diagram of the database of the application.

[0028] In the figure: 1 central control system, 2 image acquisition module, 3 image analysis unit, 31 conversion module, 32 coordinate generation module, 33 scanning module, 34 region division module, 4 model construction unit, 41 formula generation module, 42 substitution module, 43 calculation module, 44 noise point judgment module, 5 denoising module, 6 comparison module, 7 database, 71 storage module, 72 classification module, 73 deletion module, 74 receiving module, 75 protection module, 8 man-machine interaction unit, 81 face recognition module, 82 login module, 83 touch interaction module, 9 wireless transmission module, 10 display module. DETAILED DESCRIPTION

[0029] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the application.

[0030] Please refer to Figures 1-5 The embodiments of the application provide a technical solution:

[0031] As Figure 1As shown, a computer-based image processing denoising device, including central control system 1, central control system 1 is connected with image acquisition module 2 through wireless two-way connection, the output of image acquisition module 2 is electrically connected with the input of image analysis unit 3, central control system 1 is connected with model construction unit 4 through wireless two-way connection, the output of model construction unit 4 is electrically connected with the input of denoising module 5, central control system 1 is connected with contrast module 6 through wireless two-way connection, central control system 1 is connected with database 7 through wireless two-way connection, central control system 1 is connected with man-machine interaction unit 8 through wireless two-way connection, central control system 1 is connected with wireless transmission module 9 through wireless two-way connection, wireless transmission module 9 is connected with display module 10 through wireless two-way connection.

[0032] In the embodiment of the application, the output of the image analysis unit 3 is electrically connected with the input of the central control system 1, and the denoising module 5 is connected with the central control system 1 through wireless two-way connection.

[0033] As shown in the figure, Figure 2 In the embodiment of the application, the image analysis unit 3 includes a conversion module 31, a coordinate generation module 32, a scanning module 33 and a region division module 34. The conversion module 31 is used to convert a digital image into two-dimensional image information, the scanning module 33 is used to globally and locally scan the features of the two-dimensional image, and the omnibearing scanning makes the image recognition more accurate. The image is regarded as a two-dimensional matrix, the coordinate generation module 32 generates a coordinate position, and directly obtains a pixel value corresponding to the coordinate position. The region division module 34 is used to divide the matrix into a window size of 5*5.

[0034] As shown in the figure, Figure 3 In the embodiment of the application, the model construction unit 4 includes a formula generation module 41, a substitution module 42, a calculation module 43 and a noise point judgment module 44. The formula generation module 41 is used to generate a weighted formula, the substitution module 42 is used to substitute the related values of the formula, the calculation module 43 is used to calculate the formula, and the noise point judgment module 44 is used to judge whether it is noise.

[0035] As shown in the figure, Figure 4 In the embodiment of the application, the man-machine interaction unit 8 includes a face recognition module 81, a login module 82 and a touch interaction module 83. The user performs face recognition through the face recognition module 81, after successful recognition, the login module 82 is used for user login system, and the security of the system is improved. The touch interaction module 83 is used for user to perform instruction control on the display screen.

[0036] As shown in the figure, Figure 5As shown, in the embodiment of the present application, the database 7 comprises a storage module 71, the storage module 71 is bidirectionally connected with the classification module 72 wirelessly, and the storage module 71 is bidirectionally connected with the deletion module 73 wirelessly.

[0037] In the embodiment of the present application, the input end of the storage module 71 is electrically connected with the output end of the receiving module 74, the storage module 71 is bidirectionally connected with the protection module 75 wirelessly. The receiving module 74 is used for receiving image information, the storage module 71 is used for saving the denoised image and the original image, facilitating subsequent tracing, the classification module 72 separately saves the denoised image and the original image, facilitating subsequent extraction, and the deletion module 73 is used for deleting the expired image in the storage module 71, expanding the storage space.

[0038] The present application further discloses a computer-based image processing denoising method, which specifically comprises the following steps:

[0039] S1, the image acquisition module 2 is used for acquiring a digital image and uploading the digital image to an image analysis unit 3, a conversion module 31 is used for converting the digital image into two-dimensional image information, a scanning module 33 is used for globally and locally scanning the features of the two-dimensional image, and omnibearing scanning makes the image recognition more accurate, the image is regarded as a two-dimensional matrix, a coordinate generation module 32 generates a coordinate position, a pixel value corresponding to the coordinate position is directly obtained, and a region division module 34 is used for dividing the matrix into a window size of 5*5, the weight value of the point at the outermost edge is 1, and the weight of the point close to the center is 2.

[0040] S2, a formula generation module 41 is used for generating a weighted formula:

[0041]

[0042] Wherein, β represents a pixel value of a center point, X i represents pixel values of four points except the center point in the direction, W i represents a distance weight, and the closer to the center point, the greater the weight.

[0043] A substitution module 42 is used for substituting relevant numerical values of the formula, a calculation module 43 is used for calculating the formula, the difference value of the pixel value of each direction pixel and the center point pixel value in each direction is calculated for each pixel point, after calculating the weighted sum of the four lines, when the minimum value of the four weighted sums is also greater than a threshold value, the threshold value needs to be adjusted by oneself, it is indicated that the difference of each direction and the center point is relatively large, a noise judgment module 44 judges that it is noise, otherwise, it is an edge or a flat area.

[0044] S3, after judging, the denoising module 5 is used for denoising the image according to the result of the noise judging module 44, the denoised image and the original image are transmitted to the database 7, the receiving module 74 is used for receiving image information, the storage module 71 is used for saving the denoised image and the original image, facilitating subsequent tracing, the classification module 72 saves the denoised image and the original image separately, facilitating subsequent extraction, and the deleting module 73 is used for deleting the expired image in the storage module 71, expanding the storage space;

[0045] S4, the denoised image is uploaded to the central control system 1, the comparison module 6 is used for comparing the denoised image with the original image, facilitating user comparison and viewing, the wireless transmission module 9 is used for uploading the denoised image to the display module 10, and the display module 10 is used for displaying the denoised image;

[0046] S5, the user performs face recognition through the face recognition module 81, after successful recognition, the login module 82 is used for user login system, improving the security of the system, and the touch interaction module 83 is used for user instruction control on the display screen.

[0047] Meanwhile, the contents not described in detail in the specification all belong to the prior art known to those skilled in the art.

[0048] It should be noted that, in this paper, relationship terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between the entities or operations. Moreover, the term "include", "contain" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or equipment.

[0049] Although the embodiments of the present application have been shown and described, it can be understood by those skilled in the art that various changes, modifications, replacements and variations can be made to the embodiments without departing from the principles and spirits of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A computer-based image processing denoising device comprising a central control system (1), characterized in that: The central control system (1) is connected with the image acquisition module (2) by wireless, the output of the image acquisition module (2) is electrically connected with the input of the image analysis unit (3), the central control system (1) is connected with the model construction unit (4) by wireless, the output of the model construction unit (4) is electrically connected with the input of the denoising module (5), the central control system (1) is connected with the contrast module (6) by wireless, the central control system (1) is connected with the database (7) by wireless, the central control system (1) is connected with the man-machine interaction unit (8) by wireless, the central control system (1) is connected with the wireless transmission module (9) by wireless, the wireless transmission module (9) is connected with the display module (10) by wireless; The image analysis unit (3) includes conversion module (31), coordinate generation module (32), scanning module (33) and region division module (34); the conversion module (31) is used for converting digital image into two-dimensional image information, the scanning module (33) is used for globally scanning and locally scanning the features of two-dimensional image, and the image recognition is more accurate through all-around scanning; the coordinate generation module (32) generates coordinate position, and directly obtains pixel value corresponding to the coordinate position; and the region division module (33) is used for dividing the matrix into 5*5 window size; The model construction unit (4) includes formula generation module (41), substitution module (42), calculation module (43) and noise judgment module (44); the formula generation module (41) is used for generating weighted formula; the substitution module (42) is used for substituting relevant values of the formula; the calculation module (43) is used for calculating the formula; and the noise judgment module (44) is used for judging whether it is noise or not; The formula generation module (41) in the model construction unit (4) is used for generating weighted formula; the substitution module (42) is used for substituting relevant values of the formula; the calculation module (43) is used for calculating the formula; the difference value of each direction pixel and the center point pixel value in four directions is calculated for each pixel point; after calculating the weighted sum of four lines, when the minimum value of the four weighted sums is also greater than the threshold value, it is indicated that the difference of each direction with the center point is relatively large, the noise judgment module (44) judges that it is noise, otherwise it is edge or flat area; The formula generation module is used for generating weighted formula; where β represents the pixel value of the center point, X i represents the pixel value of the four points other than the center point in this direction, W i represents the distance weight, and the closer to the center point, the greater the weight.

2. The computer-based image processing denoising device according to claim 1, characterized in that: The output of the image analysis unit (3) is electrically connected with the input of the central control system (1), and the denoising module (5) is connected with the central control system (1) by wireless.

3. The computer-based image processing denoising device of claim 1, wherein: The human-computer interaction unit (8) comprises a face recognition module (81), a login module (82) and a touch interaction module (83); a user performs face recognition through the face recognition module (81), after successful recognition, the login module (82) is used for user login system, the security of the system is improved, and the touch interaction module (83) is used for user instruction control on the display screen.

4. The computer-based image processing denoising device of claim 1, wherein: The database (7) comprises a storage module (71), the storage module (71) is bidirectionally connected with the classification module (72) wirelessly, and the storage module (71) is bidirectionally connected with the deletion module (73) wirelessly; the input end of the storage module (71) is electrically connected with the output end of the receiving module (74), the receiving module (74) is used for receiving image information, the storage module (71) is used for saving the denoised image and the original image, so that subsequent tracing is facilitated, the classification module (72) separately saves the denoised image and the original image, so that subsequent extraction is facilitated, and the deletion module (73) is used for deleting expired images in the storage module (71), thereby expanding the storage space.

5. A computer-based image processing denoising method, characterized in that, The method is used for the image processing denoising device in claim 1, and specifically comprises the following steps: S1, the image acquisition module (2) is used for acquiring a digital image and uploading to the image analysis unit (3), the conversion module (31) is used for converting the digital image into two-dimensional image information, the scanning module (33) is used for globally and locally scanning the features of the two-dimensional image, the image is regarded as a two-dimensional matrix, the coordinate generation module (32) generates a coordinate position, directly obtains a pixel value corresponding to the coordinate position, and the region division module (34) is used for dividing the matrix into a 5*5 window size; S2, the formula generation module (41) in the model construction unit (4) is used for generating a weighted formula, the substitution module (42) is used for substituting relevant values of the formula, and the calculation module (43) is used for calculating the formula, calculating the weighted sum of the difference values of each direction pixel and the center point pixel value in four directions for each pixel point, after calculating the weighted sum on the four lines, when the minimum value of the four weighted sums is also greater than a threshold value, it is indicated that the difference of each direction from the center point is relatively large, the noise judgment module (44) judges that it is noise, otherwise, it is an edge or a flat area; S3, after the judgment is completed, the denoising module (5) is used for denoising the image according to the result of the noise judgment module (44), the denoised image and the original image are transmitted to the database (7), the receiving module (74) is used for receiving image information, the storage module (71) is used for saving the denoised image and the original image, the classification module (72) separately saves the denoised image and the original image, and the deletion module (73) is used for deleting expired images in the storage module (71). S4, the image after denoising is uploaded to the central control system (1), the comparison module (6) is used for comparing the image after denoising with the original image, the wireless transmission module (9) is used for uploading the image after denoising to the display module (10), and the display module (10) is used for displaying the image after denoising; S5, the user performs face recognition through the face recognition module (81), and after successful recognition, the login module (82) is used for user login system, and the touch interaction module (83) is used for user instruction control on the display screen.

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