CN110611816A - Big data compression coding method - Google Patents
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- CN110611816A CN110611816A CN201910160109.4A CN201910160109A CN110611816A CN 110611816 A CN110611816 A CN 110611816A CN 201910160109 A CN201910160109 A CN 201910160109A CN 110611816 A CN110611816 A CN 110611816A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T9/00—Image coding
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/20—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using video object coding
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/20—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using video object coding
- H04N19/23—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using video object coding with coding of regions that are present throughout a whole video segment, e.g. sprites, background or mosaic
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/85—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using pre-processing or post-processing specially adapted for video compression
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N5/00—Details of television systems
- H04N5/14—Picture signal circuitry for video frequency region
- H04N5/20—Circuitry for controlling amplitude response
- H04N5/202—Gamma control
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N5/00—Details of television systems
- H04N5/14—Picture signal circuitry for video frequency region
- H04N5/20—Circuitry for controlling amplitude response
- H04N5/205—Circuitry for controlling amplitude response for correcting amplitude versus frequency characteristic
- H04N5/208—Circuitry for controlling amplitude response for correcting amplitude versus frequency characteristic for compensating for attenuation of high frequency components, e.g. crispening, aperture distortion correction
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
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Abstract
The invention relates to a big data compression coding method, which comprises the following steps: using coding processing equipment, and carrying out MPEG-4 compression coding processing on each vehicle body sub-image with the corresponding incomplete vehicle when a first detection instruction is received so as to obtain corresponding coded image data; the monitoring server is used to receive the respective encoded image data. The big data compression coding method is widely applied and has a certain automation level.
Description
Technical Field
The invention relates to the field of big data coding, in particular to a big data compression coding method.
Background
A compression coding technique of multimedia data is developed on the basis of the c.e. shannon information theory. Coding methods can be divided into three categories: (1) according to the statistical characteristics of the information source, methods (first generation coding methods) such as predictive coding, transform coding, vector quantization coding, subband coding, neural network coding, and the like are employed. (2) According to the visual characteristics of human eyes, methods (second generation coding methods) such as image coding based on directional filtering, image contour-ethic coding based on image contour, coding based on wavelet analysis, and the like are adopted. (3) According to the delivered scene features: fractal coding, model-based coding, and the like (second generation coding methods) are employed.
Disclosure of Invention
According to an aspect of the present invention, there is provided a big data compression encoding method, the method including:
using coding processing equipment for carrying out MPEG-4 compression coding processing on each vehicle body sub-image with incomplete corresponding vehicle when a first detection instruction is received so as to obtain corresponding coded image data;
the monitoring server is arranged at the far end of the button imaging equipment, is connected with the coding processing equipment through a wireless network and is used for receiving each coded image data;
the button imaging equipment is arranged in the traffic management station and used for carrying out real-time imaging operation on the current scene of the traffic management station so as to obtain a real-time scene image;
the data volume measuring equipment is connected with the button imaging equipment and used for receiving the real-time scene image, counting the data volume of the real-time scene image and sending a first control command when the counted data volume exceeds the limit;
the data quantity measuring equipment is also used for sending a second control command when the counted data quantity is not over-limit;
in the data amount measuring apparatus, the counting the data amount of the real-time scene image includes: identifying each redundant pixel point and each non-redundant pixel point in the real-time scene image, and calculating the data volume of the real-time scene image based on the product of the number of each non-redundant pixel point in the real-time scene image and the number of bits occupied by a single pixel point;
the gamma correction equipment is also used for exiting the working mode and stopping receiving the real-time scene image when receiving the second control command;
and using a gamma correction device for entering an operation mode to receive the real-time scene image from the data quantity measuring device when the first control command is received, and executing gamma correction processing on the real-time scene image to obtain a gamma correction image.
The present invention needs to have at least the following three important points:
(1) the shapes of all images on site are analyzed simultaneously for completeness, so that the incomplete vehicle images are coded and then sent to a monitoring server, thereby improving the monitoring efficiency and ensuring the safety of vehicle road driving;
(2) on the basis of gamma correction and real-time sharpening, a self-adaptive filtering strategy is adopted for the image according to the specific content of the image so as to reduce filtering time and ensure the filtering effect;
(3) and identifying each redundant pixel point and each non-redundant pixel point in the image, and calculating the data volume of the image based on the product of the number of each non-redundant pixel point in the image and the number of bits occupied by a single pixel point.
The big data compression coding method is widely applied and has a certain automation level. The shapes of all the images on site are analyzed simultaneously, so that the incomplete vehicle images are coded and then sent to the monitoring server, the monitoring efficiency is improved, and the safety of vehicle road driving is ensured.
Detailed Description
Embodiments of the present invention will be described in detail below.
The monitoring system develops till now, except for continuous innovation of monitoring technology, a monitoring product also begins to form a powerful security monitoring system with other products, for example, an electronic fence can be utilized to enclose a monitored area into a closed area, the electronic fence is provided with a stopping and alarming system, the electronic fence is an active intrusion-preventing fence, countermeasures are made to intrusion attempts, an intruder is knocked down, the intrusion time is delayed, the life of people is not threatened, once people invade, the system starts alarming, the monitoring system also monitors at the same time, and an intrusion signal is sent to monitoring equipment of a security department, so that managers can know the condition of the alarming area in time, and the monitoring system can rapidly process the situation.
In the running process of the vehicle, in order to ensure the running safety of the vehicle and accurately obtain various auxiliary parameter information, some vehicle monitoring systems are set up to carry out monitoring operations with different purposes.
Incomplete vehicle when going on the road, will bring serious traffic hidden danger, bring danger and uncertainty for other vehicles and pedestrian, among the prior art, still rely on each traffic node's managers to carry out manual detection to the integrality detection of vehicle, efficiency is not high and lead to easily louing to examine, consequently, needs an efficient automated inspection scheme.
In order to overcome the defects, the invention builds a big data compression coding method, and can effectively solve the corresponding technical problem.
The big data compression coding device shown according to the embodiment of the invention comprises:
the encoding processing equipment is used for carrying out MPEG-4 compression encoding processing on each vehicle body sub-image with the corresponding vehicle incomplete when receiving a first detection instruction so as to obtain corresponding encoded image data;
the monitoring server is arranged at the far end of the button imaging equipment, is connected with the coding processing equipment through a wireless network and is used for receiving each coded image data;
the button imaging equipment is arranged in the traffic management station and is used for carrying out real-time imaging operation on the current scene of the traffic management station so as to obtain a real-time scene image;
the data quantity measuring equipment is connected with the button imaging equipment and used for receiving the real-time scene image, counting the data quantity of the real-time scene image and sending a first control command when the counted data quantity exceeds the limit;
the data quantity measuring equipment is also used for sending a second control command when the counted data quantity is not over-limit;
in the data amount measuring apparatus, the counting the data amount of the real-time scene image includes: identifying each redundant pixel point and each non-redundant pixel point in the real-time scene image, and calculating the data volume of the real-time scene image based on the product of the number of each non-redundant pixel point in the real-time scene image and the number of bits occupied by a single pixel point;
the gamma correction equipment is also used for exiting the working mode and stopping receiving the real-time scene image when receiving the second control command;
the gamma correction device is used for entering an operating mode to receive the real-time scene image from the data quantity measuring device when the first control command is received, and performing gamma correction processing on the real-time scene image to obtain a gamma correction image;
the real-time sharpening device is connected with the gamma correction device and is used for receiving the gamma correction image and carrying out real-time sharpening processing on the gamma correction image so as to obtain a corresponding real-time sharpened image;
the brightness analyzing device is connected with the real-time sharpening device and used for receiving the real-time sharpened image, obtaining hue component values, brightness component values and saturation component values of all pixel points in the real-time sharpened image, obtaining a first channel image based on the hue component values of all the pixel points, obtaining a second channel image based on the brightness component values of all the pixel points and obtaining a third channel image based on the saturation component values of all the pixel points;
the filtering execution device is connected with the brightness analysis device and used for executing maximum filtering processing on the third channel image to obtain a filtering processing image, and superposing the first channel image, the second channel image and the filtering processing image to obtain a filtering execution image;
the wiener filtering equipment is connected with the filtering execution equipment and used for receiving the filtering execution image and executing wiener filtering processing on the filtering execution image so as to obtain and output a wiener filtering image;
the integrity detection equipment is respectively connected with the coding processing equipment and the wiener filtering equipment and is used for identifying each vehicle body subimage in the wiener filtering image based on vehicle body imaging characteristics and identifying the appearance of each vehicle body subimage to determine whether the corresponding vehicle is complete or not, and when the vehicle corresponding to the vehicle body subimage is incomplete, a first detection instruction is sent out, otherwise, a second detection instruction is sent out;
wherein the encoding processing device is further configured not to perform any compression encoding processing of the image upon receiving the second detection instruction.
Next, a detailed configuration of the large data compression/encoding device of the present invention will be further described.
In the large data compression encoding apparatus:
the gamma correction device, the real-time sharpening device, the brightness analysis device, the filtering execution device and the wiener filtering device are respectively realized by adopting different ASIC chips;
wherein the gamma correction device, the real-time sharpening device, the brightness analyzing device, the filtering execution device, and the wiener filtering device share a same 32-bit data bus.
The big data compression encoding device may further include:
the adaptive filtering device is connected with the filtering execution device and used for receiving the filtering execution image and executing adaptive filtering processing on the filtering execution image to obtain an adaptive filtering image;
and the data sharpening device is connected with the self-adaptive filtering device and is used for receiving the self-adaptive filtering image and carrying out data sharpening processing on the self-adaptive filtering image so as to obtain a corresponding data sharpened image.
The big data compression encoding device may further include:
the contrast analysis device is connected with the data sharpening device and used for receiving the data sharpened image and executing contrast analysis operation on the data sharpened image to obtain the contrast of the data sharpened image to be used as reference contrast to be output;
wherein, in the contrast resolution device, performing a contrast resolution operation on the data sharpened image to obtain a contrast of the data sharpened image to output as a reference contrast comprises: and acquiring each Y component value of each pixel point in the data sharpening image, forming each Y component value into a Y component image, determining the contrast of the Y component image and outputting the Y component image as the reference contrast.
The big data compression encoding device may further include:
the parameter comparison equipment is connected with the contrast analysis equipment and used for receiving the reference contrast and comparing the reference contrast with a contrast threshold so as to send a first comparison instruction when the reference contrast is greater than or equal to the contrast threshold and send a second comparison instruction when the reference contrast is less than the contrast threshold;
the bright-dark level enhancement device is respectively connected with the parameter comparison device and the contrast resolution device, and is used for executing image bright-dark level enhancement processing on the data sharpened image to obtain a level enhanced image when receiving the second comparison instruction, and is also used for taking the data sharpened image as the level enhanced image when receiving the first control instruction;
wherein, a RAM unit is also arranged in the parameter comparison equipment and is used for storing the contrast threshold;
the shading hierarchy enhancement device is also connected with the wiener filtering device and used for sending the hierarchy enhancement image to the wiener filtering device in place of the filtering execution image.
The big data compression coding method according to the embodiment of the invention comprises the following steps:
using coding processing equipment for carrying out MPEG-4 compression coding processing on each vehicle body sub-image with incomplete corresponding vehicle when a first detection instruction is received so as to obtain corresponding coded image data;
the monitoring server is arranged at the far end of the button imaging equipment, is connected with the coding processing equipment through a wireless network and is used for receiving each coded image data;
the button imaging equipment is arranged in the traffic management station and used for carrying out real-time imaging operation on the current scene of the traffic management station so as to obtain a real-time scene image;
the data volume measuring equipment is connected with the button imaging equipment and used for receiving the real-time scene image, counting the data volume of the real-time scene image and sending a first control command when the counted data volume exceeds the limit;
the data quantity measuring equipment is also used for sending a second control command when the counted data quantity is not over-limit;
in the data amount measuring apparatus, the counting the data amount of the real-time scene image includes: identifying each redundant pixel point and each non-redundant pixel point in the real-time scene image, and calculating the data volume of the real-time scene image based on the product of the number of each non-redundant pixel point in the real-time scene image and the number of bits occupied by a single pixel point;
the gamma correction equipment is also used for exiting the working mode and stopping receiving the real-time scene image when receiving the second control command;
using a gamma correction device for entering an operation mode to receive the real-time scene image from the data quantity measuring device when receiving the first control command, and performing gamma correction processing on the real-time scene image to obtain a gamma corrected image;
using a real-time sharpening device connected with the gamma correction device and used for receiving the gamma correction image and carrying out real-time sharpening processing on the gamma correction image to obtain a corresponding real-time sharpened image;
using a brightness analysis device, connected to the real-time sharpening device, for receiving the real-time sharpened image, obtaining hue component values, brightness component values, and saturation component values of each pixel point in the real-time sharpened image, obtaining a first channel image based on the hue component values of each pixel point, obtaining a second channel image based on the brightness component values of each pixel point, and obtaining a third channel image based on the saturation component values of each pixel point;
using a filtering execution device connected to the luminance analysis device, for executing maximum filtering processing on the third channel image to obtain a filtering processed image, and superimposing the first channel image, the second channel image, and the filtering processed image to obtain a filtering execution image;
using a wiener filtering device connected to the filtering execution device, for receiving the filtering execution image and executing wiener filtering processing on the filtering execution image to obtain and output a wiener filtering image;
using integrity detection equipment which is respectively connected with the coding processing equipment and the wiener filtering equipment and used for identifying each vehicle body subimage in the wiener filtering image based on vehicle body imaging characteristics and carrying out shape identification on each vehicle body subimage to determine whether the corresponding vehicle is complete or not, and sending a first detection instruction when the vehicle corresponding to the vehicle body subimage is incomplete, or sending a second detection instruction when the vehicle corresponding to the vehicle body subimage is not complete;
wherein the encoding processing device is further configured not to perform any compression encoding processing of the image upon receiving the second detection instruction.
Next, the detailed steps of the big data compression encoding method of the present invention will be further described.
The big data compression coding method comprises the following steps:
the gamma correction device, the real-time sharpening device, the brightness analysis device, the filtering execution device and the wiener filtering device are respectively realized by adopting different ASIC chips;
wherein the gamma correction device, the real-time sharpening device, the brightness analyzing device, the filtering execution device, and the wiener filtering device share a same 32-bit data bus.
The big data compression coding method may further include:
using an adaptive filtering device connected to the filtering execution device, for receiving the filtering execution image, and performing adaptive filtering processing on the filtering execution image to obtain an adaptive filtering image;
and the data sharpening device is connected with the adaptive filtering device and used for receiving the adaptive filtering image and carrying out data sharpening processing on the adaptive filtering image to obtain a corresponding data sharpened image.
The big data compression coding method may further include:
using a contrast resolution device, connected to the data sharpening device, for receiving the data sharpened image, and performing a contrast resolution operation on the data sharpened image to obtain a contrast of the data sharpened image to output as a reference contrast;
wherein, in the contrast resolution device, performing a contrast resolution operation on the data sharpened image to obtain a contrast of the data sharpened image to output as a reference contrast comprises: and acquiring each Y component value of each pixel point in the data sharpening image, forming each Y component value into a Y component image, determining the contrast of the Y component image and outputting the Y component image as the reference contrast.
The big data compression coding method may further include:
the use parameter comparison equipment is connected with the contrast resolution equipment and used for receiving the reference contrast and comparing the reference contrast with a contrast threshold so as to send a first comparison instruction when the reference contrast is greater than or equal to the contrast threshold and send a second comparison instruction when the reference contrast is less than the contrast threshold;
using a bright-dark level enhancement device which is respectively connected with the parameter comparison device and the contrast resolution device, and is used for executing image bright-dark level enhancement processing on the data sharpened image when receiving the second comparison instruction to obtain a level enhanced image, and also used for taking the data sharpened image as the level enhanced image when receiving the first control instruction;
wherein, a RAM unit is also arranged in the parameter comparison equipment and is used for storing the contrast threshold;
the shading hierarchy enhancement device is also connected with the wiener filtering device and used for sending the hierarchy enhancement image to the wiener filtering device in place of the filtering execution image.
In addition, the integrity detection device is a GPU chip. . A Graphics processor (abbreviated as GPU), also called a display core, a visual processor, and a display chip, is a microprocessor specially used for image operation on a personal computer, a workstation, a game machine, and some mobile devices (such as a tablet computer and a smart phone).
The graphic processor is used for converting and driving display information required by a computer system, providing a line scanning signal for the display and controlling the correct display of the display, is an important element for connecting the display and a personal computer mainboard, and is also one of important equipment for man-machine conversation. The display card is an important component in the computer host, takes charge of outputting display graphics, and is very important for people engaged in professional graphic design.
The processor of the graphics card is called the Graphics Processor (GPU), which is the "heart" of the graphics card, similar to the CPU, except that the GPU is designed specifically to perform the complex mathematical and geometric calculations necessary for graphics rendering. Some of the fastest GPUs integrate even more transistors than normal CPUs.
Most current GPUs have 2D or 3D graphics acceleration capabilities. If the CPU wants to draw a two-dimensional graph, only an instruction needs to be sent to the GPU, for example, if a rectangle with the length and width of a multiplied by b is drawn at a coordinate position (x, y), the GPU can quickly calculate all pixels of the graph, draw a corresponding graph at a specified position on a display, inform the CPU that the graph is drawn completely, and then wait for the CPU to send a next graph instruction.
Finally, it should be noted that each functional device in the embodiments of the present invention may be integrated into one processing device, or each device may exist alone physically, or two or more devices may be integrated into one device.
The functions, if implemented in the form of software-enabled devices and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (5)
1. A big data compression coding method, characterized in that the method comprises:
using coding processing equipment for carrying out MPEG-4 compression coding processing on each vehicle body sub-image with incomplete corresponding vehicle when a first detection instruction is received so as to obtain corresponding coded image data;
the monitoring server is arranged at the far end of the button imaging equipment, is connected with the coding processing equipment through a wireless network and is used for receiving each coded image data;
the button imaging equipment is arranged in the traffic management station and used for carrying out real-time imaging operation on the current scene of the traffic management station so as to obtain a real-time scene image;
the data volume measuring equipment is connected with the button imaging equipment and used for receiving the real-time scene image, counting the data volume of the real-time scene image and sending a first control command when the counted data volume exceeds the limit;
the data quantity measuring equipment is also used for sending a second control command when the counted data quantity is not over-limit;
in the data amount measuring apparatus, the counting the data amount of the real-time scene image includes: identifying each redundant pixel point and each non-redundant pixel point in the real-time scene image, and calculating the data volume of the real-time scene image based on the product of the number of each non-redundant pixel point in the real-time scene image and the number of bits occupied by a single pixel point;
the gamma correction equipment is also used for exiting the working mode and stopping receiving the real-time scene image when receiving the second control command;
using a gamma correction device for entering an operation mode to receive the real-time scene image from the data quantity measuring device when receiving the first control command, and performing gamma correction processing on the real-time scene image to obtain a gamma corrected image;
using a real-time sharpening device connected with the gamma correction device and used for receiving the gamma correction image and carrying out real-time sharpening processing on the gamma correction image to obtain a corresponding real-time sharpened image;
using a brightness analysis device, connected to the real-time sharpening device, for receiving the real-time sharpened image, obtaining hue component values, brightness component values, and saturation component values of each pixel point in the real-time sharpened image, obtaining a first channel image based on the hue component values of each pixel point, obtaining a second channel image based on the brightness component values of each pixel point, and obtaining a third channel image based on the saturation component values of each pixel point;
using a filtering execution device connected to the luminance analysis device, for executing maximum filtering processing on the third channel image to obtain a filtering processed image, and superimposing the first channel image, the second channel image, and the filtering processed image to obtain a filtering execution image;
using a wiener filtering device connected to the filtering execution device, for receiving the filtering execution image and executing wiener filtering processing on the filtering execution image to obtain and output a wiener filtering image;
using integrity detection equipment which is respectively connected with the coding processing equipment and the wiener filtering equipment and used for identifying each vehicle body subimage in the wiener filtering image based on vehicle body imaging characteristics and carrying out shape identification on each vehicle body subimage to determine whether the corresponding vehicle is complete or not, and sending a first detection instruction when the vehicle corresponding to the vehicle body subimage is incomplete, or sending a second detection instruction when the vehicle corresponding to the vehicle body subimage is not complete;
wherein the encoding processing device is further configured not to perform any compression encoding processing of the image upon receiving the second detection instruction.
2. The big data compression encoding method of claim 1, wherein:
the gamma correction device, the real-time sharpening device, the brightness analysis device, the filtering execution device and the wiener filtering device are respectively realized by adopting different ASIC chips;
wherein the gamma correction device, the real-time sharpening device, the brightness analyzing device, the filtering execution device, and the wiener filtering device share a same 32-bit data bus.
3. The big data compression encoding method of claim 2, wherein the method further comprises:
using an adaptive filtering device connected to the filtering execution device, for receiving the filtering execution image, and performing adaptive filtering processing on the filtering execution image to obtain an adaptive filtering image;
and the data sharpening device is connected with the adaptive filtering device and used for receiving the adaptive filtering image and carrying out data sharpening processing on the adaptive filtering image to obtain a corresponding data sharpened image.
4. The big data compression encoding method of claim 3, wherein the method further comprises:
using a contrast resolution device, connected to the data sharpening device, for receiving the data sharpened image, and performing a contrast resolution operation on the data sharpened image to obtain a contrast of the data sharpened image to output as a reference contrast;
wherein, in the contrast resolution device, performing a contrast resolution operation on the data sharpened image to obtain a contrast of the data sharpened image to output as a reference contrast comprises: and acquiring each Y component value of each pixel point in the data sharpening image, forming each Y component value into a Y component image, determining the contrast of the Y component image and outputting the Y component image as the reference contrast.
5. The big data compression encoding method of claim 4, wherein the method further comprises:
the use parameter comparison equipment is connected with the contrast resolution equipment and used for receiving the reference contrast and comparing the reference contrast with a contrast threshold so as to send a first comparison instruction when the reference contrast is greater than or equal to the contrast threshold and send a second comparison instruction when the reference contrast is less than the contrast threshold;
using a bright-dark level enhancement device which is respectively connected with the parameter comparison device and the contrast resolution device, and is used for executing image bright-dark level enhancement processing on the data sharpened image when receiving the second comparison instruction to obtain a level enhanced image, and also used for taking the data sharpened image as the level enhanced image when receiving the first control instruction;
wherein, a RAM unit is also arranged in the parameter comparison equipment and is used for storing the contrast threshold;
the shading hierarchy enhancement device is also connected with the wiener filtering device and used for sending the hierarchy enhancement image to the wiener filtering device in place of the filtering execution image.
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Application publication date: 20191224 |