Image enhancement mode selection system using intelligent analysis

Abstract

The present invention relates to an image enhancement mode selection system using intelligent analysis, comprising: a visual capture device for visual capture processing of the indoor environment of the cab of a freight vehicle; an algorithm analysis device for intelligently analyzing the contrast of the image content obtained after using the enhancement algorithm based on the picture content data of the continuous optimized image obtained after the indoor environment image optimization processing, the distribution information of the continuous optimized image, and the algorithm numerical value corresponding to the enhancement algorithm to be used. The image enhancement mode selection system using intelligent analysis of the present invention has a compact structure and is easy to operate. Since various enhancement algorithms can be respectively input into a deep neural network model to obtain each contrast respectively, the enhancement algorithm corresponding to the contrast with the smallest numerical value is applied to the continuous optimized image to perform enhancement processing, so as to obtain and output the best enhanced image matching the continuous optimized image, thereby providing the best enhancement algorithm suitable for each frame of monitoring image.

Description

Technical Field

[0001] The present invention relates to the field of intelligent analysis, and in particular to an image enhancement mode selection system utilizing intelligent analysis. Background Art

[0002] Freight vehicles are cargo vehicles, generally referred to as trucks or trucks, including dump trucks, tractor trucks, off-road trucks for off-road and roadless areas, and various vehicles made for special needs. Refers to cars that are mainly used to transport goods, and sometimes also refers to cars that can tow other vehicles, belonging to the category of commercial vehicles. Generally, they can be divided into heavy and light according to the weight of the vehicle. Most trucks use diesel engines as their power source, but some light trucks use gasoline, LPG or natural gas.

[0003] Due to the characteristics of freight vehicles such as heavy loads, large size and difficulty in driving, visual monitoring of various aspects of freight vehicles is an application area that freight vehicle managers focus on developing. For example, visual capture and processing of the indoor environment of the cab of a freight vehicle is performed to obtain and output the corresponding indoor environment image. However, the content of the indoor environment images corresponding to different times is different, resulting in the final image quality often not being optimized if the same enhancement algorithm is used to perform the same enhancement processing on all indoor environment images. Therefore, it is necessary to find an enhancement algorithm that can obtain the best image quality for indoor environment images at different times, which is one of the technical problems that need to be solved at present. Summary of the invention

[0004] In order to solve the technical problems in the prior art, the present invention provides an image enhancement mode selection system using intelligent analysis, which can input various enhancement algorithms into a deep neural network model to obtain each contrast respectively, and apply the enhancement algorithm corresponding to the contrast with the smallest value to the continuously optimized image to perform enhancement processing to obtain and output the best enhanced image matching the continuously optimized image, and wirelessly send the best enhanced image of the continuously optimized image to a remote vehicle management server through a wireless transmission link via a wireless transmission interface, thereby providing each frame of the monitoring image with the best enhancement algorithm suitable for itself.

[0005] According to the present invention, there is provided an image enhancement mode selection system using intelligent analysis, the system comprising:

[0006] A speed measuring device is arranged in the freight vehicle, and is used to measure the current travel speed of the freight vehicle, and to send a first measurement signal when the measured current travel speed of the freight vehicle is greater than or equal to a set speed threshold;

[0007] A visual capture device, disposed in the cab of the freight vehicle and connected to the speed measurement device, for starting visual capture processing of the indoor environment of the cab upon receiving the first measurement signal, so as to obtain and output a corresponding indoor environment image;

[0008] A continuous optimization device, connected to the visual capture device and comprising a front-end optimization device, a mid-end optimization device and a terminal optimization device, for continuously performing a non-scaling transformation blur process, a spatial differential method sharpening process and a Gaussian high-pass filter process on the received indoor environment image to obtain and output a corresponding continuous optimization image;

[0009] A component extraction device, connected to the continuous optimization device, for detecting the hue component value, brightness component value and saturation component value of each pixel in the received continuous optimization image in the HSL space, and outputting the hue component value, brightness component value and saturation component value of each pixel in the continuous optimization image as the picture content data of the continuous optimization image;

[0010] A noise identification device is used to detect noise data corresponding to each type of noise among various types of noise appearing in the continuous optimized image, wherein the noise data corresponding to each type of noise is a noise amplitude corresponding to each type of noise and the number of associated pixels, and output the noise data of each type of noise in the continuous optimized image as distribution information of the continuous optimized image;

[0011] An algorithm analysis device, connected to the component extraction device and the noise identification device respectively, for synchronously inputting into a deep neural network model based on the picture content data of the continuously optimized image, the distribution information of the continuously optimized image and the algorithm numerical representation corresponding to the enhancement algorithm to be used to obtain the contrast of the image content obtained after the continuous optimized image uses the enhancement algorithm, wherein the deep neural network model is a deep neural network after multiple learning;

[0012] The algorithm analysis device is further used to input various enhancement algorithms into the deep neural network model to obtain the contrast of each portion respectively, and apply the enhancement algorithm corresponding to the contrast with the smallest value to the continuously optimized image to perform enhancement processing, so as to obtain and output the best enhanced image matching the continuously optimized image;

[0013] A wireless transmission interface is connected to the algorithm analysis device and is used to wirelessly send the best enhanced image of the continuously optimized image to a remote vehicle management server via a wireless transmission link.

[0014] Therefore, the present invention has at least the following four beneficial technical effects:

[0015] Technical effect A: After the monitoring screen of the indoor environment of the cab is optimized and processed, the hue component value, brightness component value and saturation component value of each pixel in the continuous optimization image obtained in the HSL space are obtained, and the hue component value, brightness component value and saturation component value of each pixel in the continuous optimization image are output as the picture content data of the continuous optimization image;

[0016] Technical effect B: detecting noise data corresponding to each type of noise appearing in a continuous optimized image, wherein the noise data corresponding to each type of noise is a noise amplitude corresponding to each type of noise and the number of associated pixels, and outputting the noise data of each type of noise in the continuous optimized image as distribution information of the continuous optimized image;

[0017] Technical effect C: Based on the picture content data of the continuously optimized image, the distribution information of the continuously optimized image and the algorithm numerical representation corresponding to the enhancement algorithm to be used, the image content contrast obtained after the continuously optimized image uses the enhancement algorithm is synchronously input into the deep neural network model, and the deep neural network model is a deep neural network after multiple learning, thereby providing key information for the selection of subsequent enhancement algorithms;

[0018] Technical effect D: Various enhancement algorithms are respectively input into the deep neural network model to obtain each contrast respectively, and the enhancement algorithm corresponding to the contrast with the smallest numerical value is applied to the continuously optimized image to perform enhancement processing to obtain and output the best enhanced image matching the continuously optimized image, and the best enhanced image of the continuously optimized image is wirelessly sent to a remote vehicle management server through a wireless transmission link via a wireless transmission interface, thereby providing each frame of the monitoring image with the best enhancement algorithm suitable for itself.

[0019] The image enhancement mode selection system using intelligent analysis of the present invention has a compact structure and is easy to operate. Since various enhancement algorithms can be input into the deep neural network model to obtain the contrast of each part respectively, the enhancement algorithm corresponding to the contrast with the smallest value is applied to the continuous optimization image to perform enhancement processing, so as to obtain and output the best enhanced image matching the continuous optimization image, thereby providing the best enhancement algorithm suitable for each frame of the monitoring image. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The embodiments of the present invention will be described below with reference to the accompanying drawings, wherein:

[0021] Figure 1 Schematic diagram of the internal structure of an image enhancement mode selection system using intelligent analysis according to Embodiment A of the present invention.

[0022] Figure 2FIG. 1 is a schematic diagram of the internal structure of an image enhancement mode selection system using intelligent analysis according to Embodiment B of the present invention.

[0023] Figure 3 Schematic diagram of the internal structure of an image enhancement mode selection system using intelligent analysis according to Embodiment C of the present invention. DETAILED DESCRIPTION

[0024] The following will describe in detail an embodiment of the image enhancement mode selection system using intelligent analysis of the present invention with reference to the accompanying drawings.

[0025] Figure 1 This is a schematic diagram of the internal structure of an image enhancement mode selection system using intelligent analysis according to Embodiment A of the present invention, wherein the system comprises:

[0026] A speed measuring device is arranged in the freight vehicle, and is used to measure the current travel speed of the freight vehicle, and to send a first measurement signal when the measured current travel speed of the freight vehicle is greater than or equal to a set speed threshold;

[0027] For example, a speed measuring device is provided in a freight vehicle, and is used to measure the current travel speed of the freight vehicle, and when the measured current travel speed of the freight vehicle is greater than or equal to a set speed threshold, a first measurement signal is sent, including: the speed measuring device includes a speed detection component and a signal triggering component connected to the speed detection component;

[0028] Specifically, the speed detection component is used to measure the current travel speed of the freight vehicle, and the signal triggering component is used to send a first measurement signal when the measured current travel speed of the freight vehicle is greater than or equal to a set speed threshold;

[0029] A visual capture device, disposed in the cab of the freight vehicle and connected to the speed measurement device, for starting visual capture processing of the indoor environment of the cab upon receiving the first measurement signal, so as to obtain and output a corresponding indoor environment image;

[0030] A continuous optimization device, connected to the visual capture device and comprising a front-end optimization device, a mid-end optimization device and a terminal optimization device, for continuously performing a non-scaling transformation blur process, a spatial differential method sharpening process and a Gaussian high-pass filter process on the received indoor environment image to obtain and output a corresponding continuous optimization image;

[0031] A component extraction device, connected to the continuous optimization device, for detecting the hue component value, brightness component value and saturation component value of each pixel in the received continuous optimization image in the HSL space, and outputting the hue component value, brightness component value and saturation component value of each pixel in the continuous optimization image as the picture content data of the continuous optimization image;

[0032] A noise identification device is used to detect noise data corresponding to each type of noise among various types of noise appearing in the continuous optimized image, wherein the noise data corresponding to each type of noise is a noise amplitude corresponding to each type of noise and the number of associated pixels, and output the noise data of each type of noise in the continuous optimized image as distribution information of the continuous optimized image;

[0033] An algorithm analysis device, connected to the component extraction device and the noise identification device respectively, for synchronously inputting into a deep neural network model based on the picture content data of the continuously optimized image, the distribution information of the continuously optimized image and the algorithm numerical representation corresponding to the enhancement algorithm to be used to obtain the contrast of the image content obtained after the continuous optimized image uses the enhancement algorithm, wherein the deep neural network model is a deep neural network after multiple learning;

[0034] The algorithm analysis device is further used to input various enhancement algorithms into the deep neural network model to obtain the contrast of each portion respectively, and apply the enhancement algorithm corresponding to the contrast with the smallest value to the continuously optimized image to perform enhancement processing, so as to obtain and output the best enhanced image matching the continuously optimized image;

[0035] A wireless transmission interface, connected to the algorithm analysis device, for wirelessly transmitting the best enhanced image of the continuously optimized image to a remote vehicle management server via a wireless transmission link;

[0036] Wherein, the continuous optimization device is connected to the visual capture device and includes a front-end optimization device, a mid-end optimization device and a terminal optimization device, and is used to continuously perform non-scaling transformation blur processing, spatial differential method sharpening processing and Gaussian high-pass filtering processing on the received indoor environment image to obtain and output the corresponding continuous optimization image, including: the front-end optimization device, the mid-end optimization device and the terminal optimization device respectively perform non-scaling transformation blur processing, spatial differential method sharpening processing and Gaussian high-pass filtering processing on the received image data;

[0037] Wherein, the speed measuring device is further used to send a second measurement signal when the measured current travel speed of the freight vehicle is less than the set speed threshold;

[0038] Wherein, the visual capture device is also used to stop executing the visual capture processing of the indoor environment of the cab when receiving the second measurement signal.

[0039] Figure 2 FIG. 1 is a schematic diagram of the internal structure of an image enhancement mode selection system using intelligent analysis according to Embodiment B of the present invention.

[0040] and Figure 1 different, Figure 2 The image enhancement mode selection system using intelligent analysis may also include the following components:

[0041] A coding operation device, connected to the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device by wires, respectively, for performing compression coding operations on the output data or input data of the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device respectively;

[0042] The encoding operation device is connected to the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device by wires, and is used to perform compression encoding operations on the output data or input data of the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device, respectively, including: the encoding operation device uses a set compression ratio to perform compression encoding operations on the output data or input data of the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device, respectively;

[0043] The encoding operation device uses a set compression ratio to perform compression encoding operations on the output data or input data of the continuous optimization device, the component extraction device, the noise identification device, and the algorithm analysis device, respectively, including: the set compression ratio used in performing compression encoding operations on the output data or input data of the continuous optimization device, the component extraction device, the noise identification device, and the algorithm analysis device, respectively, is between 0.2 and 0.5;

[0044] The encoding operation device is connected to the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device by wires, and is used to perform compression encoding operations on the output data or input data of the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device, respectively. The encoding operation device also includes: the encoding operation device includes a plurality of encoding operation units, which are used to perform compression encoding operations on the output data or input data of the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device, respectively;

[0045] And wherein, the encoding operation device includes multiple encoding operation units, which are used to perform compression encoding operations on the output data or input data of the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device respectively, including: the structures of the multiple encoding operation units are the same.

[0046] Figure 3 Schematic diagram of the internal structure of an image enhancement mode selection system using intelligent analysis according to Embodiment C of the present invention.

[0047] and Figure 1 different, Figure 3 The image enhancement mode selection system using intelligent analysis may also include the following components:

[0048] The projection operation device is respectively arranged near the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device, and is respectively connected to the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device by wire;

[0049] The projection operation device is respectively arranged near the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device, and is respectively connected to the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device by wire, including: the projection operation device is used to project and display the working status information of the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device respectively;

[0050] And wherein, the projection operation device is used to project and display the working status information of the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device respectively, including: the working status information of the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device includes the current configuration parameters and the current working mode of the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device.

[0051] In addition, in the image enhancement mode selection system using intelligent analysis, the picture content data of the continuously optimized image, the distribution information of the continuously optimized image and the algorithm numerical representation corresponding to the enhancement algorithm to be used are synchronously input into the deep neural network model to obtain the contrast of the image content obtained after the continuously optimized image uses the enhancement algorithm. The deep neural network model is a deep neural network after multiple learning, including: the number of times the deep neural network is learned is positively correlated with the contrast of the continuously optimized image.

[0052] While the invention has been particularly shown and described with reference to exemplary embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the claims.

Claims

1. An image enhancement mode selection system using intelligent analysis, characterized in that: The system comprises: A speed measuring device is arranged in the freight vehicle, and is used to measure the current travel speed of the freight vehicle, and to send a first measurement signal when the measured current travel speed of the freight vehicle is greater than or equal to a set speed threshold; A visual capture device, disposed in the cab of the freight vehicle and connected to the speed measurement device, for starting visual capture processing of the indoor environment of the cab upon receiving the first measurement signal, so as to obtain and output a corresponding indoor environment image; A continuous optimization device, connected to the visual capture device and comprising a front-end optimization device, a mid-end optimization device and a terminal optimization device, for continuously performing a non-scaling transformation blur process, a spatial differential method sharpening process and a Gaussian high-pass filter process on the received indoor environment image to obtain and output a corresponding continuous optimization image; A component extraction device, connected to the continuous optimization device, for detecting the hue component value, brightness component value and saturation component value of each pixel in the received continuous optimization image in the HSL space, and outputting the hue component value, brightness component value and saturation component value of each pixel in the continuous optimization image as the picture content data of the continuous optimization image; A noise identification device is used to detect noise data corresponding to each type of noise among various types of noise appearing in the continuous optimized image, wherein the noise data corresponding to each type of noise is a noise amplitude corresponding to each type of noise and the number of associated pixels, and output the noise data of each type of noise in the continuous optimized image as distribution information of the continuous optimized image; An algorithm analysis device, connected to the component extraction device and the noise identification device respectively, for synchronously inputting into a deep neural network model based on the picture content data of the continuously optimized image, the distribution information of the continuously optimized image and the algorithm numerical representation corresponding to the enhancement algorithm to be used to obtain the contrast of the image content obtained after the continuous optimized image uses the enhancement algorithm, wherein the deep neural network model is a deep neural network after multiple learning; The algorithm analysis device is further used to input various enhancement algorithms into the deep neural network model to obtain the contrast of each portion respectively, and apply the enhancement algorithm corresponding to the contrast with the smallest value to the continuously optimized image to perform enhancement processing, so as to obtain and output the best enhanced image matching the continuously optimized image; A wireless transmission interface is connected to the algorithm analysis device and is used to wirelessly send the best enhanced image of the continuously optimized image to a remote vehicle management server via a wireless transmission link.

2. The image enhancement mode selection system using intelligent analysis as claimed in claim 1, characterized in that: A continuous optimization device, connected to the visual capture device and including a front-end optimization device, a mid-end optimization device and a terminal optimization device, for continuously performing a non-scaling transformation blur processing, a spatial differential method sharpening processing and a Gaussian high-pass filtering processing on the received indoor environment image to obtain and output a corresponding continuous optimization image, including: the front-end optimization device, the mid-end optimization device and the terminal optimization device respectively perform a non-scaling transformation blur processing, a spatial differential method sharpening processing and a Gaussian high-pass filtering processing on the received image data; Wherein, the speed measuring device is further used to send a second measurement signal when the measured current travel speed of the freight vehicle is less than the set speed threshold; Wherein, the visual capture device is also used to stop executing the visual capture processing of the indoor environment of the cab when receiving the second measurement signal.

3. The image enhancement mode selection system using intelligent analysis as claimed in claim 2, characterized in that: The system further comprises: A coding operation device, connected to the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device by wires, respectively, for performing compression coding operations on the output data or input data of the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device respectively; Among them, the encoding operation device is respectively connected to the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device by wire, and is used to perform compression encoding operations on the output data or input data of the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device respectively, including: the encoding operation device uses a set compression ratio to perform compression encoding operations on the output data or input data of the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device respectively.

4. The image enhancement mode selection system using intelligent analysis as claimed in claim 3, characterized in that: The encoding operation device uses a set compression ratio to perform compression encoding operations on the output data or input data of the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device, including: the set compression ratio used to perform compression encoding operations on the output data or input data of the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device is between 0.2-0.

5.

5. The image enhancement mode selection system using intelligent analysis as claimed in claim 4, characterized in that: A coding operation device is respectively connected to the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device by wire, and is used to perform compression coding operations on the output data or input data of the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device respectively. The coding operation device also includes: the coding operation device includes multiple coding operation units, which are used to perform compression coding operations on the output data or input data of the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device respectively.

6. The image enhancement mode selection system using intelligent analysis as claimed in claim 5, characterized in that: The encoding operation device includes multiple encoding operation units, which are used to perform compression encoding operations on the output data or input data of the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device respectively, including: the structures of the multiple encoding operation units are the same.

7. The image enhancement mode selection system using intelligent analysis as claimed in claim 2, characterized in that: The system further comprises: The projection operation device is respectively arranged near the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device, and is respectively connected to the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device by wire.

8. The image enhancement mode selection system using intelligent analysis as claimed in claim 7, characterized in that: The projection operation device is respectively arranged near the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device, and is respectively connected to the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device by wire, including: the projection operation device is used to project and display the working status information of the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device respectively.

9. The image enhancement mode selection system using intelligent analysis as claimed in claim 8, characterized in that: The projection operation device is used to project and display the working status information of the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device respectively, including: the working status information of the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device includes the current configuration parameters and the current working mode of the continuous optimization device, the component extraction device, the noise identification device and the algorithm analysis device.

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