CN108259819B - Dynamic image feature enhancement method and system - Google Patents
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- CN108259819B CN108259819B CN201611242604.2A CN201611242604A CN108259819B CN 108259819 B CN108259819 B CN 108259819B CN 201611242604 A CN201611242604 A CN 201611242604A CN 108259819 B CN108259819 B CN 108259819B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/183—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a single remote source
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- H—ELECTRICITY
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- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/60—Control of cameras or camera modules
- H04N23/66—Remote control of cameras or camera parts, e.g. by remote control devices
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- H—ELECTRICITY
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- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
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Abstract
The invention relates to a dynamic image feature enhancement method and a system, wherein the method comprises the following steps: capturing a plurality of images from a camera; selecting an interested area from a picture of the camera through an interested area switching unit; setting a plurality of brightness weight values in the region of interest; adjusting a brightness parameter of the picture of the camera according to each brightness weight value; a multi-layer progressive sharpness process is performed by a sharpness adjustment unit to update an actual sharpness parameter of the camera. The shooting parameters of the camera are directly and instantly adjusted, parameters such as brightness or resolution of the captured image are improved, and the intelligent advanced driving assistance system can clearly identify the road and the coming vehicle of the opposite side.
Description
Technical Field
The present invention relates to a method and a system for enhancing dynamic image features, and more particularly, to a method and a system for enhancing dynamic image features capable of directly adjusting the shooting parameters of a camera.
Background
With the popularization of digital cameras in daily life and the development of computer vision, intelligent imaging technology has been applied in many fields to bring safety and convenience to human life. For example, applications of security monitoring are face recognition, fingerprint recognition, smoke detection, and the like. In the field of automotive electronics, Advanced Driver Assistance Systems (ADAS) have been rapidly developed in recent years, and it is desired to reduce the incidence of traffic accidents through the application of artificial intelligence. The intelligent advanced driving assistance system comprises a lane line detection system, a reversing assistance system, a front vehicle collision avoidance system and the like, and is a recently actively developed technology for domestic and foreign vehicle factories.
Referring to fig. 6, the conventional intelligent advanced driving assistance system 60 includes an image capturing module 61, a calculating module 62, a vehicle classifier 63, a vehicle detector 64, a warning device 65 and a display 66. The image capturing module 61 captures an image of a road ahead, the calculating module 62 is connected to the image capturing module 61 and analyzes and identifies the captured image, the vehicle classifier 63 is connected to the calculating module 62 and classifies the types of vehicles in the image so as to judge the intensity of collision, the vehicle detector 64 is connected to the calculating module 62 and is used for detecting vehicles coming ahead and coming from the other side, the warning device 65 is connected to the vehicle classifier 63 and the vehicle detector 64, when abnormal conditions (such as coming from the other side, vehicles too close to the front side or large trucks in the front) are judged, the warning device 65 gives a warning, and the display 66 is connected to the vehicle detector 64 and receives the image to display road conditions.
In the application of the intelligent advanced driving assistance system 60, image processing is the most important core technology, and the image quality determines the accuracy of the recognition result. However, in the conventional image capturing module 61, fixed camera parameters (such as fixed white balance, fixed brightness, or fixed color) are used in any situation, and the fixed camera parameters cannot be applied to various environments (such as a backlight environment, a low-light environment, or a common-light environment), so that the captured image is overexposed or the image brightness is too low, and the intelligent advanced driving assistance system 60 cannot effectively determine the coming vehicle or the obstacle, thereby causing a car accident.
Chinese patent No. CN105684417A discloses a method for adjusting restoration strength and sharpening strength, in which an edge enhancement processing unit mainly performs sharpening processing using a sharpening filter on image data, adjusts a restoration rate according to an increase or decrease in a sharpening rate, and compensates for an influence of the increase or decrease in the sharpening rate by the restoration rate, thereby stably improving the image quality of the image data. The patent focuses on edge improvement processing of the output image without improving the image brightness.
Therefore, it is necessary to invent a dynamic image feature enhancement method and system, so that the camera can automatically adjust the shooting parameters under different environments, and the intelligent advanced driving assistance system can clearly identify the road and the coming vehicle of the other party.
Disclosure of Invention
The present invention is directed to a dynamic image feature enhancement method, which can adjust the shooting parameters of a camera for different light environments, so that an intelligent advanced driving assistance system can clearly identify a road and an oncoming vehicle.
According to the above object, the present invention provides a method for enhancing features of a moving image, comprising the steps of:
capturing a plurality of images from a camera;
selecting an interested area from a picture of the camera through an interested area switching unit, and dividing the interested area into a plurality of blocks;
setting a plurality of brightness weight values in the region of interest;
adjusting a brightness parameter of the picture of the camera according to each brightness weight value;
utilizing a sharpness adjustment unit to execute a multi-layer progressive sharpness program to progressively update an actual sharpness parameter of the camera; grading the edge exposure degrees of the images presented by the picture to strengthen the outlines of the images presented by the blocks; finding out corresponding edges by using the multilayer progressive sharpness program, correcting sharpness parameters according to the damage degree of the images of the blocks, transferring the edge information of the images to a high frequency domain, dividing the edge information into multilayer edge information, and merging the multilayer edge information;
wherein, the multi-layer progressive sharpness process comprises:
setting a sharpness parameter critical value;
comparing the actual sharpness parameter with the sharpness parameter critical value, and gradually correcting the actual sharpness parameter in a step increasing and decreasing mode to be close to the sharpness parameter critical value; if the actual sharpness parameter is smaller than the sharpness parameter critical value within the difference allowable value range, increasing the actual sharpness parameter, and if the actual sharpness parameter is larger than the sharpness parameter critical value within the error allowable value range, reducing the actual sharpness parameter;
and grading the edge exposure degrees of the images presented by the frame so as to strengthen the outlines of the images presented by the blocks.
The invention has the advantages that: the shooting parameters of the camera are directly and instantly adjusted, parameters such as brightness or resolution of the captured image are improved, and the intelligent advanced driving assistance system can clearly identify the road and the coming vehicle of the opposite side.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a block diagram of a motion image feature enhancement system according to the present invention.
Fig. 2A is a schematic diagram of selecting a region of interest by a dynamic image feature enhancement method.
FIG. 2B is a diagram illustrating a weight distribution of the dynamic image feature enhancement method.
FIG. 3 is a flowchart illustrating a method for enhancing dynamic image features according to the present invention.
Fig. 4 is a flowchart of a multi-layer progressive sharpening procedure.
Fig. 5 is a schematic diagram of a multi-layer progressive sharpening process.
Fig. 6 is a system block diagram of a conventional intelligent advanced driving assistance system.
Detailed Description
The technical means adopted by the invention to achieve the predetermined object of the invention are further described below with reference to the drawings and the preferred embodiments of the invention.
Referring to fig. 1, fig. 2A and fig. 2B, the system 10 for enhancing dynamic image features of the present invention includes a camera 11, a display screen 12, a Region of Interest (ROI) switching unit 13, a block dividing unit 14, an image analyzing unit 15, a brightness weight setting unit 16, a brightness adjusting unit 17 and a sharpness adjusting unit 18.
The camera 11 can be a general digital camera or a digital video camera, the camera 11 includes a display screen 12, or the camera 11 is externally connected to the display screen 12. The camera 11 has a memory 111, and the memory 111 can store the images captured by the camera 11. The ROI switching unit 13 is electrically connected to the display screen 12, and according to different road conditions, different time or different weather, a user can switch the size of an ROI 122 of a frame 121 of the display screen 12 through the ROI switching unit 13.
The tile dividing unit 14 is electrically connected to the display screen 12, and is configured to divide the frame 121 of the display screen 12 into a plurality of tiles 123. The image analysis unit 15 is electrically connected to the camera 11, and is configured to analyze a plurality of images captured by the camera 11 for image parameters such as brightness or sharpness parameters. The brightness weight setting unit 16 is electrically connected to the image analyzing unit 15 and the display screen 12, receives a plurality of brightness parameters of the plurality of images from the image analyzing unit 15, and sets the brightness weight of each image in each block 123 of the display screen 12 by referring to a brightness weight comparison table stored in the memory 111. The cameras 11 of different brands have different brightness weight comparison tables, and through the brightness weight comparison tables, the dynamic image feature enhancement system 10 of the present invention can adjust the image to have clear and visible brightness according to the brightness range represented by each weight value, and how to design the brightness weight comparison tables is well known to those skilled in the art and will not be described herein again. The brightness adjusting unit 17 is electrically connected to the brightness weight setting unit 16 and the camera 11, and adjusts the brightness of each image of each block 123 of the screen 121 to be consistent according to the brightness weight value of each brightness of each block 123.
The sharpness adjusting unit 18 is electrically connected to the camera 11 and the image analyzing unit 15, and after the brightness adjustment, according to the sharpness parameters of the images analyzed by the image analyzing unit 15, the sharpness adjusting unit 18 uses a multi-layer progressive sharpness program to enhance the profiles of the images, and corrects the actual sharpness parameters according to the damage degree of each image of each block 123, and finally, the edge information of the images is transferred to a high frequency domain, so that the multi-layer edges of the images are merged, and the purpose of enhancing the profiles of the images is achieved.
Referring to FIG. 3 and the reference numerals of FIG. 1, the method for enhancing dynamic image features according to the present invention includes the following steps. In step S301, a camera 11 captures a plurality of images and stores the images into a memory 111, the camera 11 of the dynamic image feature enhancement system 10 continuously captures the plurality of images of the road ahead, and since the ambient brightness and the image contour do not change instantaneously, the plurality of images in the previous time interval are processed to adjust the shooting parameters of the camera 11, so that the plurality of images displayed on a display screen 12 are clearly recognizable.
In step S302, a Region of Interest (Region of Interest)122 is selected from a frame 121 of the display screen 12. In the screen 121 displayed on the display screen 12, not all regions need to be subjected to image enhancement processing, and the setting of the region of interest 122 can reduce the time for image calculation and accelerate the time for image enhancement. For example, as shown in fig. 2A, the area around the screen 121 is a tree or a stationary vehicle, and these objects are not on a vehicle driving path and do not need to be image-enhanced. Therefore, by selecting the roi 122, the range of image processing required is narrowed, and the load and time for image processing by the motion image feature enhancement system 10 are reduced.
The motion image feature enhancement system 10 can be embedded in an electronic system of a vehicle (e.g., a navigation system or a central control system), or the motion image feature enhancement system 10 can be installed in an automatic driving system of a vehicle, but is not limited thereto. Moreover, the range of the region of interest 122 is different according to different environments, and the user can adjust the range of the region of interest according to different road conditions and different visual fields.
In step S303, a plurality of brightness weight values of the frame 121 of the display screen 12 are set. After the region of interest 122 is set, the method for enhancing dynamic image features divides the frame 121 and the region of interest 122 into a plurality of blocks 123, and marks the brightness weight values of the blocks 123. In each image, not every block 123 is overexposed or underbright, but some blocks 123 are overexposed (overexposed) and some blocks 123 are too dark, so that brightness adjustment is required for each block 123. The setting of the plurality of brightness weight values may be performed by first designing a brightness weight comparison table, and referring to the brightness weight comparison table to give each brightness weight value to each block 123 according to the actual brightness value of each image of each block 123. The brightness weight comparison table may be stored in the brightness weight setting unit 16, or the brightness weight comparison table may be stored in the memory 111 of the camera 11, but is not limited thereto. The brightness weight comparison table may be different according to individual settings, and the brightness weight comparison table shown herein is only an example and is not limited to the value of the brightness weight comparison table, and the brightness weight comparison table may be different according to different vehicles and different cameras.
For example, as shown in fig. 2B, the region outside the roi 122 is not the key region of the image enhancement, and thus the brightness weight values in the region are all set to 1. In the interesting region 122, each block 123 is given a brightness weight value according to the actual brightness value, for example, the brightness weight value is 5, which indicates that the brightness of the block 123 is too dark, and the brightness weight value is 2, which indicates that the block 123 is overexposed.
In step S304, the brightness of the frame of the camera 11 is adjusted according to each of the brightness weight values. According to each brightness weight value, the brightness parameter of the picture 10 of the camera 11 is adjusted. The dynamic image feature enhancement method of the present invention adjusts the brightness of the plurality of images captured by the camera 11, and directly adjusts the brightness parameter of the camera 11, instead of adjusting the plurality of images.
In step S305, the sharpness of each image of the screen 121 of the camera 11 is adjusted. After the brightness adjustment of the frame 121 of the camera 11 is completed, the sharpness of the frame 121 of the camera 11 can be enhanced, and before the sharpness adjustment, the contour analysis of each image of the frame 121 of the camera 11 needs to be performed. According to the images captured by the camera 11, the contour analysis of each image is performed to analyze whether the edge of each image is blurred or clear.
In step S306, a sharpening parameter of the camera is updated by a multi-layer progressive sharpening process. Since the sharpness adjustment of the camera 11 of the present invention is performed by using the dynamic image feature enhancement system 10, the dynamic image feature enhancement system 10 employs a fine adjustment mechanism to gradually adjust the sharpness parameter step by step, and the sharpness parameter is adjusted slightly each time, so as to adjust the camera 11 to be within an error tolerance of a sharpness parameter threshold. The images and the sharpness parameter threshold are stored in the memory 111.
Referring to fig. 4, the multi-layered progressive sharpness process includes the following steps, in step S401, setting a sharpness parameter threshold, wherein a plurality of images of the blocks 123 of the region of interest 121 in the frame 10 of the camera 11 have different sharpness parameters, respectively, and adjusting an actual sharpness parameter of the camera according to the sharpness parameter threshold, so that the images captured by the camera 11 are all images with clear and visible outlines.
In step S402, an actual sharpness parameter is compared with the sharpness parameter threshold, and the actual sharpness parameter is gradually modified in a stepwise manner to approach the sharpness parameter threshold. The sharpness parameter critical value is a set value with clear image outline, the sharpness parameter critical value can be modified into different set values according to different users, in addition, during adjustment, an error allowable value of the sharpness parameter critical value can be set, the actual sharpness parameter of the camera is adjusted within the error allowable value range of the sharpness parameter critical value, and the image shot by the camera is clear and visible.
In step S403, if the actual sharpness parameter is smaller than the tolerance of the sharpness parameter threshold, the actual sharpness parameter is increased, otherwise, in step S404, if the actual sharpness parameter is larger than the tolerance of the sharpness parameter threshold, the actual sharpness parameter is decreased. And ending the multi-layer progressive sharpness process until the actual sharpness parameter is within the effective range of the sharpness parameter threshold.
For example, as shown in fig. 5, in one embodiment, the multi-level progressive sharpness process sets a plurality of sharpness levels (e.g., four sharpness levels, etc.) which are a first sharpness increasing layer 41, a second sharpness increasing layer 42, a first sharpness decreasing layer 51 and a second sharpness decreasing layer 52 respectively, and indicates that the sharpness parameter is increased or decreased twice each time the multi-level progressive sharpness process is performed. The sharpness increasing layers or sharpness decreasing layers with different layers can be set according to different requirements, and the more the layers are, the more the adjustment of the actual sharpness parameter to the sharpness parameter critical value can be accelerated.
For example, the sharpness parameter is set to 256 levels of 0 to 255 according to the definition of a plurality of image contours, the actual sharpness parameter of the image of a block is 200, and the sharpness parameter threshold of the motion image feature enhancement system is 231 ± 5, i.e. the actual sharpness parameter value is adjusted to be within the range of the error tolerance (between 226 and 236), the multi-level progressive sharpness process enters the first sharpness increasing layer 41, and the actual sharpness parameter is increased by 5 in the first sharpness increasing layer 41, the actual sharpness parameter is adjusted to 205, it is still smaller than the sharpness parameter threshold, so that the first sharpness increasing layer 41 is further entered to increase the actual sharpness parameter until the actual sharpness parameter is adjusted to be within the range of the error tolerance of the sharpness parameter threshold. On the contrary, if the actual sharpness parameter is greater than the sharpness parameter threshold, the first sharpness decreasing layer 51 is entered, and the actual sharpness parameter is gradually adjusted to the range of the error tolerance of the sharpness parameter threshold.
In addition, in step S306, the method further includes grading the edge exposure levels of the images displayed on the screen to enhance the outlines of the images displayed by the blocks 123. After finding out the corresponding edges by using the multi-layer progressive sharpness procedure, and correcting sharpness parameters according to the damage degree of the images of the blocks 123, the edge information of the images is finally converted to the high frequency domain and divided into multi-layer edge information, such as T1 layer edge information, T2 layer edge information, T3 layer edge information, T4 layer edge information, and the like shown in fig. 5, and the multi-layer edge information is merged to achieve the purpose of enhancing the contours of the images displayed on the screen 121. The image parameters of the camera 11 are gradually adjusted by using the images captured by the camera 11, so as to achieve the purpose of improving the adjustment of the output image of the camera 11. The parameters of the images are adjusted by a front-end adjustment method (directly adjusting the shooting parameters of the camera), rather than adjusting the brightness, contrast, or exposure parameters of the images after the images are obtained as in the prior art. Therefore, the dynamic image feature enhancement method of the present invention enables the intelligent advanced driving assistance system to immediately grasp the road condition, and make a judgment at the first time according to the plurality of images captured by the camera 11.
Although the present invention has been described with reference to a preferred embodiment, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (7)
1. A method for enhancing features of a dynamic image, comprising the steps of:
capturing a plurality of images from a camera;
selecting an interested area from a picture of the camera through an interested area switching unit, and dividing the interested area into a plurality of blocks;
setting a plurality of brightness weight values in the region of interest;
adjusting a brightness parameter of the picture of the camera according to each brightness weight value;
utilizing a sharpness adjustment unit to execute a multi-layer progressive sharpness program to progressively update an actual sharpness parameter of the camera; grading the edge exposure degrees of the images presented by the picture to strengthen the outlines of the images presented by the blocks; finding out corresponding edges by using the multilayer progressive sharpness program, correcting sharpness parameters according to the damage degree of the images of the blocks, transferring the edge information of the images to a high frequency domain, dividing the edge information into multilayer edge information, and merging the multilayer edge information;
wherein, the multi-layer progressive sharpness process comprises:
setting a sharpness parameter critical value;
comparing the actual sharpness parameter with the sharpness parameter critical value, and gradually correcting the actual sharpness parameter in a step increasing and decreasing mode to be close to the sharpness parameter critical value; if the actual sharpness parameter is smaller than the sharpness parameter critical value within an error tolerance range, increasing the actual sharpness parameter, and if the actual sharpness parameter is larger than the sharpness parameter critical value within the error tolerance range, reducing the actual sharpness parameter;
and grading the edge exposure degrees of the images presented by the frame so as to strengthen the outlines of the images presented by the blocks.
2. The method of claim 1, wherein the step of setting the brightness weight values in the region of interest further comprises: and setting each brightness weight value of each block.
3. The method of claim 1, wherein the setting of the brightness weighting values is performed according to an actual brightness value of each block and referring to a brightness weighting look-up table to give the brightness weighting value to each block.
4. The method of claim 1, wherein the plurality of images and the sharpness parameter threshold are stored in a memory.
5. A dynamic image feature enhancement system comprises:
a camera;
a display screen connected with the camera;
the interested region switching unit is electrically connected with the display screen and switches an interested region of one picture of the display screen;
the block dividing unit is electrically connected with the display screen so as to divide the picture of the display screen into a plurality of blocks;
an image analysis unit electrically connected with the camera for analyzing the brightness parameter and sharpness parameter of the images shot by the camera;
a brightness weight setting unit electrically connected with the image analysis unit and the display screen, receiving a plurality of brightness parameters of the plurality of images, and setting a brightness weight value of each image in each block of the display screen by referring to a brightness weight comparison table;
a brightness adjusting unit electrically connected with the brightness weight setting unit and the camera, and adjusting the brightness of each image of each block of the picture to be consistent according to the brightness weight value of each brightness of each block;
a sharpness adjusting unit electrically connected to the camera and the image analyzing unit, for adjusting the sharpness parameter of each image of each block to a sharpness parameter threshold, and gradually updating an actual sharpness parameter of the camera by a multi-layer progressive sharpness procedure according to the sharpness parameter of each image analyzed by the image analyzing unit, to enhance the profiles of the plurality of images, wherein the sharpness adjusting unit comprises the following steps when performing the multi-layer progressive sharpness procedure:
setting a sharpness parameter critical value;
comparing the actual sharpness parameter with the sharpness parameter critical value, and gradually correcting the actual sharpness parameter in a step increasing and decreasing mode to be close to the sharpness parameter critical value; if the actual sharpness parameter is smaller than the sharpness parameter critical value within an error tolerance range, increasing the actual sharpness parameter, and if the actual sharpness parameter is larger than the sharpness parameter critical value within the error tolerance range, reducing the actual sharpness parameter;
grading the exposure degree of the edges of the images presented by the frame, converting the edge information of the images into a high frequency domain, dividing the edge information into multiple layers of edge information, and merging the multiple layers of edge information to strengthen the outlines of the images presented by the blocks.
6. The system of claim 5, wherein the plurality of images and the sharpness parameter threshold are stored in a memory of the camera.
7. The system of claim 5, wherein the sharpness adjustment unit modifies an actual sharpness parameter according to a degree of breakage of each of the images of each of the blocks.
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