CN111429360A - Dual-display device for graphic image processing and control method thereof - Google Patents
Dual-display device for graphic image processing and control method thereof Download PDFInfo
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Abstract
The invention belongs to the technical field of image processing, and discloses a dual-display device for graphic image processing and a control method thereof, wherein the control method of the device comprises the following steps: the image denoising method comprises the steps of denoising a collected image by using a graphic image denoising module, enhancing cloud or texture of the graphic image by using a graphic image preprocessing module, increasing the dynamic range of the image by using a graphic image gray level transformation module, enabling the image to be more convenient to analyze and recognize by using a graphic image equalization module, optimizing the target and the background of the image by using a graphic image dynamic threshold segmentation module, and converting the processed graphic image into a three-dimensional image by using a graphic image transformation module. The invention has simple structure, and the displayed graphic image is correct and clear in structure by means of denoising, filtering, preprocessing, gray level transformation, contrast enhancement and image segmentation on the received graphic image, thereby being convenient for the user to recognize and understand, greatly facilitating the user and being popularized and used.
Description
Technical Field
The invention belongs to the technical field of image processing, and particularly relates to a dual-display device for graphic image processing and a control method thereof.
Background
Currently, the closest prior art: image processing, a technique of analyzing an image with a computer to achieve a desired result, is also called image processing. Image processing generally refers to digital image processing. Digital images are large two-dimensional arrays of elements called pixels and values called gray-scale values, which are captured by industrial cameras, video cameras, scanners, etc. Image processing techniques generally include image compression, enhancement and restoration, matching, description and identification of 3 parts.
The dynamic range based on conventional displays can distinguish a processed image from the same image viewed in the real world, but is generally insufficient to cause the optical perception of viewing an image in the real world, and although some image enhancement methods have been devised to create a more realistic image impression, limitations in the dynamic range of conventional display devices cause even the enhanced image to appear inconsistent with the real world image.
In summary, the problems of the prior art are as follows: limitations in the dynamic range of conventional display devices make even the enhanced image appear to be inconsistent with the real world image.
Disclosure of Invention
To solve the problems of the prior art, the present invention provides a dual display apparatus for graphic image processing and a control method thereof.
The present invention is achieved in that a control method of a dual display device for graphic image processing, the control method of the dual display device for graphic image processing includes the steps of:
carrying out denoising processing on a received graphic image by a non-local average filtering and denoising method through a graphic image denoising program, (I) carrying out preliminary denoising processing on an acquired image to be processed by an N L M algorithm to obtain a preliminary denoised image;
(II) calculating residual error quantities of central pixels of each unit area corresponding to the image to be processed according to the numerical values of the specific energy parameters corresponding to the image to be processed and the preliminary denoising image respectively;
(III) calculating a weight matrix corresponding to each unit region by using the residual quantity, and performing non-local mean calculation on the image to be processed according to the weight matrix so as to realize the denoising processing of the image to be processed.
Step two, increasing the dynamic range of the image by using a piecewise linear gray scale conversion method; carrying out defogging enhancement processing on the graphic image by an image enhancement program: (1) carrying out calculation processing on the foggy image by using a non-local prior algorithm to obtain a first fusion image;
(2) calculating the hazy image by using an automatic color gradation algorithm to obtain a second fused image;
(3) and fusing the first fused image and the second fused image by taking the transmissivity image as a weight to obtain a fog-free image.
Step three, the master controller is used for controlling an image equalization processing program to enhance the contrast of the image by using a histogram processing method; the objects and background of the image are optimized by a dynamic threshold segmentation procedure using a dynamic threshold segmentation method.
Step four, converting the processed graphic image into a three-dimensional image by using a convolution neural network, matching and other modes: 1) performing edge detection on the two-dimensional target image, determining the edge of a target object in the two-dimensional target image through edge detection, and then further determining the position of the target object according to the edge of the target object;
2) performing feature extraction on the two-dimensional target image by adopting a convolutional neural network, wherein the extracted content comprises attribute information of target objects and relative positions and sizes among the target objects;
3) and determining a target three-dimensional image corresponding to the target object according to the attribute information of the target object.
Step five, supporting by using an adjustable bracket and adjusting the height of the device so as to scan display images with various heights; and receiving the processed graphic image information through the mobile terminal, and performing remote control on the dual-display device.
Sixthly, supplying power to the double-display device through a built-in storage battery and an external power supply lead; the image information and the processed image state of the received and transmitted image are displayed through the double display screens and the operation buttons, and the image contrast in the processing process can be checked.
Further, in the first step, the method for performing preliminary denoising processing on the acquired image to be processed by using the N L M algorithm in the step (I) is as follows:
for noisy images y (i) ═ x (i) + N (i), x (i) is the original image, N (i) is noise, and the dessicated images recovered by the N L M algorithm are:
w (i, j) is a gray value similarity weight between pixel points i and j, A is the image size, B is a similarity neighborhood window with the current pixel point as the center, h is a filtering control parameter, the size of h controls the filtering degree, and n (B) is the number of pixel points in the neighborhood window B.
Further, in step one, the method for calculating the weight matrix in step (III) includes:
selecting any unit area on the image to be processed, and determining a relevant area of the unit area on the image to be processed; calculating a weight value corresponding to each associated unit region according to a distance value between each associated unit region in the associated regions and any unit region and the residual quantity to obtain the weight matrix;
the process of the non-local mean calculation comprises:
and calculating the weighted sum of all pixels in the associated region according to the corresponding relation between each associated unit region in the associated region and the weight value in the weight matrix, wherein the weighted sum is used as a result of denoising the central pixel of any unit region.
Further, in the second step, the method for increasing the dynamic range of the image by using the piecewise linear gray scale conversion specifically includes:
1) the piecewise transformation method has the following specific functional formula:
4) in the above equation, f (x, y) represents the original image, g (x, y) represents the image obtained after the conversion, and in the piecewise linear gray scale conversion, the range of the useful gray scale of the image can be expanded by carefully adjusting the node positions and controlling the slopes of piecewise straight lines.
Further, in step three, the method for enhancing the contrast of the image by the histogram processing through the image equalization processing program specifically includes:
1) the method formula for calculating the histogram of the original image is shown as the following graph:
where N is the total number of original pixels, L is the maximum value of gray scale, rkRepresenting the kth grey level, nkRepresenting the number of occurrences of k gray levels in the graph, P (r)k) If yes, representing the probability of gray level occurrence;
2) calculating the gray scale accumulation distribution function S of the original image according to a probability formulakThen, a gray level conversion table is calculated according to the formula as follows:
5) the inverse transformation from S to r is:
r＝T-1(s)，0≤s≤1。
further, in step three, the method for optimizing the target and background of the image by the dynamic threshold segmentation process using the dynamic threshold segmentation method comprises:
1) a digital image with L gray levels in size (M × N) may be represented as I ═ { f (x, y) }, where x is 1 … M and y is 1 … N, let G ═ 0,1,2.. L-1 } be the set of image gray levels, then f (x, y) ∈ G represents the gray level of the pixel at coordinates (x, y), and G (x, y) represents the domain average gray level at the pixel point (x, y), and G (x, y) is calculated by:
2) the method for constructing a two-dimensional histogram of an image using the pixel gray f (x, y) of the image and the corresponding neighborhood average gray g (x, y) is as follows:
h(m，n)＝Prob(f(x，y)＝m&g(x，y)＝n)；
wherein m, n belong to a set G of image gray levels;
3) the normalized two-dimensional histogram approximation formula is as follows:
wherein E ism，nThe number of pixels representing a pixel with a gray level of M and a neighborhood with an average gray level of N, where M × N is the total number of pixels in the image.
Further, in the fourth step, the method for establishing the three-dimensional image specifically comprises the following steps:
firstly, establishing a three-dimensional image library, wherein the three-dimensional image library comprises various three-dimensional images, such as three-dimensional images corresponding to people, cats, dogs, bicycles, flowers, clouds and the like, in specific implementation, some basic geometric elements in a three-dimensional modeling tool, such as cubes and spheres, are adopted, and complex three-dimensional images are constructed through a series of geometric operations, such as translation, rotation, stretching, Boolean operation and the like; the three-dimensional modeling tools include DMAX, Softimage, Maya, UG, and AutoCAD.
Another object of the present invention is to provide a dual display device for graphic image processing to which the control method of the dual display device for graphic image processing is applied, characterized in that the dual display device for graphic image processing comprises:
the device comprises a wireless signal transceiving module, a graphic image denoising module, a graphic image gray level conversion module, a graphic image preprocessing module, a main control module, a graphic image equalization module, a graphic image dynamic threshold segmentation module, a graphic image conversion module, a support module, a terminal module, a power supply module and a double-display module.
The wireless signal transceiver module is connected with the main control module and is used for transceiving the graphic image information through the wireless signal transceiver;
the image de-noising module is connected with the main control module and is used for de-noising the received image by a non-local average filtering and drying method through an image de-noising program;
the graphic image gray level conversion module is connected with the main control module and is used for increasing the dynamic range of the image by utilizing a piecewise linear gray level conversion method;
the graphics image preprocessing module is connected with the main control module and is used for performing defogging enhancement processing on the graphics image through an image enhancement program;
the main control module is connected with the wireless signal transceiving module, the graphic image denoising module, the graphic image gray level conversion module, the graphic image preprocessing module, the graphic image equalization module, the graphic image dynamic threshold segmentation module, the graphic image conversion module, the support module, the terminal module, the power supply module and the double display module and is used for controlling the normal operation of each module through the main controller;
the graphic image equalization module is connected with the main control module and used for enhancing the contrast of the image by utilizing a histogram processing method through an image equalization processing program;
a dynamic threshold partitioning module, coupled to the main control module, for optimizing the target and background of the image by a dynamic threshold partitioning method through a dynamic threshold partitioning procedure;
the graphic image conversion module is connected with the main control module and converts the processed graphic image into a three-dimensional image by using a convolution neural network, matching and other modes;
the supporting module is connected with the main control module, is supported by the adjustable bracket and can adjust the height of the device so as to scan display images with various heights;
the terminal module is connected with the main control module and used for receiving the processed graphic image information through the mobile terminal and carrying out remote control on the dual-display device;
the power supply module is connected with the main control module and used for supplying power to the dual-display device through the built-in storage battery and the external power supply lead;
and the double-display module is connected with the main control module and used for displaying the received and sent graphic image information and the processed image state through the double display screens and the operation buttons and checking the image contrast in the processing process.
It is another object of the present invention to provide a computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface to implement the method for controlling a dual display device for graphic image processing when executed on an electronic device.
Another object of the present invention is to provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method for controlling a dual display device for graphic image processing.
In summary, the advantages and positive effects of the invention are: the invention adopts the image denoising module to denoise the acquired image, can keep the detail characteristics of the image as much as possible, and enables the denoised image to look more natural. The image preprocessing module is used for enhancing the cloud and fog or the texture of the image, and the image with fog can be defogged, so that the definition and the contrast of the image are improved, and the visual experience of the image is optimized. The dynamic range of the image is enlarged by adopting the graphic image gray level conversion module, the image is more convenient to analyze and recognize by adopting the graphic image equalization module, the target and the background of the image are optimized by adopting the graphic image dynamic threshold segmentation module, and the processed graphic image is converted into a three-dimensional image by adopting the graphic image conversion module. The invention has simple structure, and the displayed graphic image is correct and has clear structure by means of denoising, filtering, preprocessing, gray level transformation, contrast enhancement and image segmentation on the received graphic image, so that the enhanced image is consistent with the real world image, and the invention is convenient for the user to identify and understand, greatly facilitates the user and can be popularized and used.
Drawings
Fig. 1 is a flowchart of a control method of a dual display device for graphic image processing according to an embodiment of the present invention.
FIG. 2 is a block diagram of a dual display device for graphics image processing according to an embodiment of the present invention;
in the figure: 1. a wireless signal transceiving module; 2. a graphic image denoising module; 3. a graphic image gray level conversion module; 4. a graphics image preprocessing module; 5. a main control module; 6. a graphic image equalization module; 7. a pattern dynamic threshold partitioning block; 8. a graphic image conversion module; 9. a support module; 10. a terminal module; 11. a power supply module; 12. and a dual display module.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In view of the problems in the prior art, the present invention provides a dual display device for graphic image processing and a control method thereof, and the technical solution of the present invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, a method for controlling a dual display device for graphic image processing according to an embodiment of the present invention includes the steps of:
s101, receiving and transmitting graphic image information through a wireless signal transceiver; and denoising the received graphic image by a graphic image denoising program by using a non-local average filtering and denoising method.
S102, increasing the dynamic range of the image by using a piecewise linear gray scale conversion method; and carrying out defogging enhancement processing on the graphic image through an image enhancement program.
S103, controlling the normal operation of the double-display device through the main controller; the contrast of the image is enhanced by a histogram processing method through an image equalization processing program.
S104, optimizing the target and the background of the image by a dynamic threshold segmentation program through a dynamic threshold segmentation method; and converting the processed graphic image into a three-dimensional image by using a convolution neural network, matching and other modes.
S105, supporting and adjusting the height of the device by using an adjustable bracket so as to scan display images with various heights; and receiving the processed graphic image information through the mobile terminal, and performing remote control on the dual-display device.
S106, supplying power to the double-display device through the built-in storage battery and the external power supply lead; the image information and the processed image state of the received and transmitted image are displayed through the double display screens and the operation buttons, and the image contrast in the processing process can be checked.
As shown in fig. 2, the dual display apparatus for graphic image processing according to the embodiment of the present invention includes: the device comprises a wireless signal transceiving module 1, a graphic image denoising module 2, a graphic image gray level conversion module 3, a graphic image preprocessing module 4, a main control module 5, a graphic image equalization module 6, a graphic image dynamic threshold segmentation module 7, a graphic image conversion module 8, a support module 9, a terminal module 10, a power supply module 11 and a double display module 12.
The wireless signal transceiver module 1 is connected with the main control module 5 and is used for transceiving graphic image information through a wireless signal transceiver;
the image de-noising module 2 is connected with the main control module 5 and is used for de-noising the received image by a non-local average filtering and de-drying method through an image de-noising program;
the graphic image gray level conversion module 3 is connected with the main control module 5 and used for increasing the dynamic range of the image by utilizing a piecewise linear gray level conversion method;
the graphic image preprocessing module 4 is connected with the main control module 5 and is used for performing defogging enhancement processing on the graphic image through an image enhancement program;
the main control module 5 is connected with the wireless signal transceiving module 1, the graphic image denoising module 2, the graphic image gray level conversion module 3, the graphic image preprocessing module 4, the graphic image equalization module 6, the graphic image dynamic threshold segmentation module 7, the graphic image conversion module 8, the support module 9, the terminal module 10, the power supply module 11 and the double display module 12 and is used for controlling the normal operation of each module through the main controller;
the graphic image equalization module 6 is connected with the main control module 5 and is used for enhancing the contrast of the image by utilizing a histogram processing method through an image equalization processing program;
a dynamic threshold pattern segmentation module 7 connected to the main control module 5 for optimizing the target and background of the image by a dynamic threshold segmentation process;
the graphic image conversion module 8 is connected with the main control module 5 and converts the processed graphic image into a three-dimensional image by using a convolution neural network, matching and other modes;
the supporting module 9 is connected with the main control module 5, supports the device by using an adjustable bracket and can adjust the height of the device so as to scan display images with various heights;
the terminal module 10 is connected with the main control module 5 and used for receiving the processed graphic image information through the mobile terminal and carrying out remote control on the dual-display device;
the power supply module 11 is connected with the main control module 5 and used for supplying power to the dual-display device through a built-in storage battery and an external power supply lead;
and the double-display module 12 is connected with the main control module 5 and is used for displaying the received and sent graphic image information and the processed image state through a double display screen and an operation button and checking the image contrast in the processing process.
The invention is further described with reference to specific examples.
Example 1
Fig. 1 shows a control method of a dual-display device for processing a graphic image according to an embodiment of the present invention, and as a preferred embodiment, the method for performing denoising processing on a received graphic image by using a non-local average filtering and drying method through a graphic image denoising program according to an embodiment of the present invention includes:
(I) and carrying out primary denoising processing on the acquired image to be processed by utilizing an N L M algorithm to obtain a primary denoised image.
(II) calculating residual quantity of central pixels of each unit area on the image to be processed according to the numerical values of the specific energy parameters respectively corresponding to the image to be processed and the preliminary denoising image.
(III) calculating a weight matrix corresponding to each unit region by using the residual quantity, and performing non-local mean calculation on the image to be processed according to the weight matrix so as to realize the denoising processing of the image to be processed.
The method for performing preliminary denoising processing on the acquired image to be processed by using the N L M algorithm in the step (I) provided by the embodiment of the invention is as follows:
for noisy images y (i) ═ x (i) + N (i), x (i) is the original image, N (i) is noise, and the dessicated images recovered by the N L M algorithm are:
w (i, j) is a gray value similarity weight between pixel points i and j, A is the image size, B is a similarity neighborhood window with the current pixel point as the center, h is a filtering control parameter, the size of h controls the filtering degree, and n (B) is the number of pixel points in the neighborhood window B.
The method for calculating the weight matrix in the step (III) provided by the embodiment of the present invention includes: selecting any unit area on the image to be processed, and determining a relevant area of the unit area on the image to be processed; calculating a weight value corresponding to each associated unit region according to a distance value between each associated unit region and any unit region in the associated regions and the residual quantity to obtain the weight matrix.
The process of calculating the non-local mean value provided by the embodiment of the invention comprises the following steps: and calculating the weighted sum of all pixels in the associated region according to the corresponding relation between each associated unit region in the associated region and the weight value in the weight matrix, wherein the weighted sum is used as a result of denoising the central pixel of any unit region.
Example 2
As shown in fig. 1, a control method of a dual display device for graphics image processing according to an embodiment of the present invention is that, as a preferred embodiment, a method for performing a defogging enhancement process on a graphics image by an image enhancement program according to an embodiment of the present invention includes:
(1) and carrying out calculation processing on the foggy image by using a non-local prior algorithm to obtain a first fusion image.
(2) And calculating the hazy image by using an automatic color gradation algorithm to obtain a second fused image.
(3) And fusing the first fused image and the second fused image by taking the transmissivity image as a weight to obtain a fog-free image.
Example 3
Fig. 1 shows a control method of a dual display device for graphic image processing according to an embodiment of the present invention, and as a preferred embodiment, the method for increasing a dynamic range of an image by using a piecewise linear gray scale transformation according to the embodiment of the present invention specifically includes the following steps:
1) the piecewise transformation method has the following specific functional formula:
2) in the above equation, f (x, y) represents the original image, g (x, y) represents the image obtained after the conversion, and in the piecewise linear gray scale conversion, the range of the useful gray scale of the image can be expanded by carefully adjusting the node positions and controlling the slopes of piecewise straight lines.
Example 4
Fig. 1 shows a control method of a dual display device for graphics image processing according to an embodiment of the present invention, and as a preferred embodiment, the method for enhancing contrast of an image by using a histogram processing method through an image equalization processing program according to an embodiment of the present invention specifically includes the following steps:
1) the method formula for calculating the histogram of the original image is shown as the following graph:
where N is the total number of original pixels, L is the maximum value of gray scale, rkRepresenting the kth grey level, nkRepresenting the number of occurrences of k gray levels in the graph, P (r)k) Is then the probability of the occurrence of a gray level.
2) Calculating the gray scale accumulation distribution function S of the original image according to a probability formulakThen, a gray level conversion table is calculated according to the formula as follows:
3) the inverse transformation from S to r is:
r＝T-1(s)，0≤s≤1。
example 5
Referring to fig. 1, a method for controlling a dual display device for graphic image processing according to an embodiment of the present invention is disclosed, which is a preferred embodiment of a method for optimizing an object and a background of an image by a dynamic threshold segmentation process according to an embodiment of the present invention, and the method comprises:
1) a digital image with L gray levels in size (M × N) may be represented as I ═ { f (x, y) }, where x is 1 … M and y is 1 … N, let G ═ 0,1,2.. L-1 } be the set of image gray levels, then f (x, y) ∈ G represents the gray level of the pixel at coordinates (x, y), and G (x, y) represents the domain average gray level at the pixel point (x, y), and G (x, y) is calculated by:
2) the method for constructing a two-dimensional histogram of an image using the pixel gray f (x, y) of the image and the corresponding neighborhood average gray g (x, y) is as follows:
h(m，n)＝Prob(f(x，y)＝m&g(x，y)＝n)；
where m, n belong to the set of image gray levels G.
3) The normalized two-dimensional histogram approximation formula is as follows:
wherein E ism，nThe number of pixels representing a pixel with a gray level of M and a neighborhood with an average gray level of N, where M × N is the total number of pixels in the image.
Example 6
Fig. 1 shows a control method of a dual display device for graphics image processing according to an embodiment of the present invention, and as a preferred embodiment, the method for converting a processed graphics image into a three-dimensional image by using a convolutional neural network and a matching method according to an embodiment of the present invention includes:
1) and performing edge detection on the two-dimensional target image, determining the edge of the target object in the two-dimensional target image through the edge detection, and further determining the position of the target object according to the edge of the target object.
2) And performing feature extraction on the two-dimensional target image by adopting a convolutional neural network, wherein the extracted content comprises attribute information of the target object and the relative position and size between the target objects.
3) And determining a target three-dimensional image corresponding to the target object according to the attribute information of the target object.
The method for establishing the three-dimensional image provided by the embodiment of the invention specifically comprises the following steps:
firstly, establishing a three-dimensional image library, wherein the three-dimensional image library comprises various three-dimensional images, such as three-dimensional images corresponding to people, cats, dogs, bicycles, flowers, clouds and the like, in specific implementation, some basic geometric elements in a three-dimensional modeling tool, such as cubes and spheres, are adopted, and complex three-dimensional images are constructed through a series of geometric operations, such as translation, rotation, stretching, Boolean operation and the like; the three-dimensional modeling tools include DMAX, Softimage, Maya, UG, and AutoCAD.
The computer instructions may be stored on or transmitted from one computer-readable storage medium to another computer-readable storage medium, e.g., from one website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DS L) or wireless (e.g., infrared, wireless, microwave, etc.) means to another website site, computer, server, or data center via a solid state storage medium, such as a solid state Disk, or the like, (e.g., a solid state Disk, a magnetic storage medium, such as a DVD, a SSD, etc.), or any combination thereof.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. A control method of a dual display device for graphic image processing, characterized in that the control method of a dual display device for graphic image processing comprises the steps of:
carrying out denoising processing on a received graphic image by a non-local average filtering and denoising method through a graphic image denoising program, (I) carrying out preliminary denoising processing on an acquired image to be processed by an N L M algorithm to obtain a preliminary denoised image;
(II) calculating residual error quantities of central pixels of each unit area corresponding to the image to be processed according to the numerical values of the specific energy parameters corresponding to the image to be processed and the preliminary denoising image respectively;
(III) calculating a weight matrix corresponding to each unit region by using the residual quantity, and performing non-local mean calculation on the image to be processed according to the weight matrix so as to realize denoising processing on the image to be processed;
step two, increasing the dynamic range of the image by using a piecewise linear gray scale conversion method; carrying out defogging enhancement processing on the graphic image by an image enhancement program: (1) carrying out calculation processing on the foggy image by using a non-local prior algorithm to obtain a first fusion image;
(2) calculating the hazy image by using an automatic color gradation algorithm to obtain a second fused image;
(3) fusing the first fused image and the second fused image by taking the transmissivity image as a weight to obtain a fog-free image;
step three, the master controller is used for controlling an image equalization processing program to enhance the contrast of the image by using a histogram processing method; optimizing the target and background of the image by a dynamic threshold segmentation procedure using a dynamic threshold segmentation method;
step four, converting the processed graphic image into a three-dimensional image by using a convolutional neural network and a matching mode: 1) performing edge detection on the two-dimensional target image, determining the edge of a target object in the two-dimensional target image through edge detection, and then further determining the position of the target object according to the edge of the target object;
2) performing feature extraction on the two-dimensional target image by adopting a convolutional neural network, wherein the extracted content comprises attribute information of target objects and relative positions and sizes among the target objects;
3) determining a target three-dimensional image corresponding to the target object according to the attribute information of the target object;
step five, supporting by using an adjustable bracket and adjusting the height of the device so as to scan display images with various heights; receiving the processed graphic image information through the mobile terminal, and performing remote control on the dual-display device;
sixthly, supplying power to the double-display device through a built-in storage battery and an external power supply lead; the image information and the processed image state of the received and transmitted image are displayed through the double display screens and the operation buttons, and the image contrast in the processing process can be checked.
2. The method for controlling a dual display device for graphic image processing as claimed in claim 1, wherein in step one, the method of step (I) for performing preliminary denoising processing on the acquired image to be processed by using N L M algorithm comprises the following steps:
for noisy images y (i) ═ x (i) + N (i), x (i) is the original image, N (i) is noise, and the dessicated images recovered by the N L M algorithm are:
w (i, j) is a gray value similarity weight between pixel points i and j, A is the image size, B is a similarity neighborhood window with the current pixel point as the center, h is a filtering control parameter, the size of h controls the filtering degree, and n (B) is the number of pixel points in the neighborhood window B.
3. The method for controlling a dual display device for graphic image processing according to claim 1, wherein in step one, the method for calculating the weight matrix of step (III) comprises:
selecting any unit area on the image to be processed, and determining a relevant area of the unit area on the image to be processed; calculating a weight value corresponding to each associated unit region according to a distance value between each associated unit region in the associated regions and any unit region and the residual quantity to obtain the weight matrix;
the process of the non-local mean calculation comprises:
and calculating the weighted sum of all pixels in the associated region according to the corresponding relation between each associated unit region in the associated region and the weight value in the weight matrix, wherein the weighted sum is used as a result of denoising the central pixel of any unit region.
4. The method for controlling a dual display device for graphic image processing according to claim 1, wherein in the second step, the method for increasing the dynamic range of the image by using the piecewise linear gray scale transformation specifically comprises the following steps:
1) the piecewise transformation method has the following specific functional formula:
2) in the above equation, f (x, y) represents the original image, g (x, y) represents the image obtained after the conversion, and in the piecewise linear gray scale conversion, the range of the useful gray scale of the image can be expanded by carefully adjusting the node positions and controlling the slopes of piecewise straight lines.
5. The method for controlling a dual display device for graphic image processing according to claim 1, wherein in step three, the method for enhancing the contrast of the image by the histogram processing through the image equalization processing procedure specifically comprises the following steps:
1) the method formula for calculating the histogram of the original image is shown as the following graph:
where N is the total number of original pixels, L is the maximum value of gray scale, rkRepresenting the kth grey level, nkRepresenting the number of occurrences of k gray levels in the graph, P (r)k) If yes, representing the probability of gray level occurrence;
2) calculating the gray scale accumulation distribution function S of the original image according to a probability formulakThen, a gray level conversion table is calculated according to the formula as follows:
3) the inverse transformation from S to r is:
r＝T-1(s)，0≤s≤1。
6. the method of claim 1, wherein in step three, the process of optimizing the object and background of the image by threshold segmentation using a threshold segmentation method comprises:
1) a digital image with L gray levels in size (M × N) may be represented as I ═ { f (x, y) }, where x is 1 … M and y is 1 … N, let G ═ 0,1,2.. L-1 } be the set of image gray levels, then f (x, y) ∈ G represents the gray level of the pixel at coordinates (x, y), and G (x, y) represents the domain average gray level at the pixel point (x, y), and G (x, y) is calculated by:
2) the method for constructing a two-dimensional histogram of an image using the pixel gray f (x, y) of the image and the corresponding neighborhood average gray g (x, y) is as follows:
h(m，n)＝Pr ob(f(x，y)＝m&g(x，y)＝n)；
wherein m, n belong to a set G of image gray levels;
3) the normalized two-dimensional histogram approximation formula is as follows:
wherein E ism.nThe number of pixels representing a pixel with a gray level of M and a neighborhood with an average gray level of N, where M × N is the total number of pixels in the image.
7. The method for controlling a dual display device for graphics image processing according to claim 1, wherein in step four, the method for creating the three-dimensional image is as follows:
firstly, establishing a three-dimensional image library, wherein the three-dimensional image library comprises various three-dimensional images, such as three-dimensional images corresponding to people, cats, dogs, bicycles, flowers, clouds and the like, in specific implementation, some basic geometric elements in a three-dimensional modeling tool, such as cubes and spheres, are adopted, and complex three-dimensional images are constructed through a series of geometric operations, such as translation, rotation, stretching, Boolean operation and the like; the three-dimensional modeling tools include DMAX, Softimage, Maya, UG, and AutoCAD.
8. A dual display device for graphic image processing to which the control method of a dual display device for graphic image processing according to any one of claims 1 to 7 is applied, comprising:
the wireless signal transceiver module is connected with the main control module and is used for transceiving the graphic image information through the wireless signal transceiver;
the image de-noising module is connected with the main control module and is used for de-noising the received image by a non-local average filtering and drying method through an image de-noising program;
the graphic image gray level conversion module is connected with the main control module and is used for increasing the dynamic range of the image by utilizing a piecewise linear gray level conversion method;
the graphics image preprocessing module is connected with the main control module and is used for performing defogging enhancement processing on the graphics image through an image enhancement program;
the main control module is connected with the wireless signal transceiving module, the graphic image denoising module, the graphic image gray level conversion module, the graphic image preprocessing module, the graphic image equalization module, the graphic image dynamic threshold segmentation module, the graphic image conversion module, the support module, the terminal module, the power supply module and the double display module and is used for controlling the normal operation of each module through the main controller;
the graphic image equalization module is connected with the main control module and used for enhancing the contrast of the image by utilizing a histogram processing method through an image equalization processing program;
a dynamic threshold partitioning module, coupled to the main control module, for optimizing the target and background of the image by a dynamic threshold partitioning method through a dynamic threshold partitioning procedure;
the graphic image conversion module is connected with the main control module and is used for converting the processed graphic image into a three-dimensional image by utilizing a convolutional neural network and a matching mode;
the supporting module is connected with the main control module, is supported by the adjustable bracket and can adjust the height of the device so as to scan display images with various heights;
the terminal module is connected with the main control module and used for receiving the processed graphic image information through the mobile terminal and carrying out remote control on the dual-display device;
the power supply module is connected with the main control module and used for supplying power to the dual-display device through the built-in storage battery and the external power supply lead;
and the double-display module is connected with the main control module and used for displaying the received and sent graphic image information and the processed image state through the double display screens and the operation buttons and checking the image contrast in the processing process.
9. A computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface for implementing a method of controlling a dual display device for graphic image processing according to any one of claims 1 to 7 when executed on an electronic device.
10. A computer-readable storage medium storing instructions which, when executed on a computer, cause the computer to execute the method for controlling a dual display device for graphic image processing according to any one of claims 1 to 7.
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