CN106454014B - A kind of method and device improving backlight scene vehicle snapshot picture quality - Google Patents
A kind of method and device improving backlight scene vehicle snapshot picture quality Download PDFInfo
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Abstract
The invention discloses a kind of method and apparatus for improving backlight scene vehicle snapshot picture quality, this method and device carry out backlight processing to luminance Y component using grayscale mapping curve, have adjusted the dark space of image reversible-light shooting, improve the visual effect of dark space, color component is corrected in combination with the backlight degree for the treatment of of luminance Y component, the color saturation of image is avoided to change with bright-colored degree.Compared with prior art, the present invention enhances the candid photograph effect of backlight scene according to image local feature information self-adapting, while promoting backlight dark picture areas details, can preferably retain highlighted details and Image Warping.Realize that simply adaptivity is strong, improves universality and validity that traffic route video camera captures image processing method under backlight scene on engineer application.
Description
Technical field
The present invention relates to the video image processing technology of intelligent transportation field more particularly to a kind of raising backlight
The method and device of scene vehicle snapshot picture quality.
Background technique
As modern transportation Road Development and Intelligent traffic management systems are universal, the traffic safety the aobvious important.Electronics is alert
It examines, intelligent high definition bayonet, disobey and stop the householder methods such as evidence obtaining, radar overspeed snapping in intelligent transportation field performance key effect.
The candid camera installed in ordinary road, due to the constraint by extraneous light environment, image quality can go out
Existing decay, influences effective evidence obtaining of illegal vehicle.In China's most area, for the traffic route of east-west direction, road
Road vehicles, which capture image, often will appear backlight scene, that is, the Vehicle Object that is taken causes to capture along the direction running of light
Vehicle characteristics details in image frame cannot be showed effectively.It is primarily due in video imaging system, generallys use
Exposal control method is automated using the average brightness and static exposure reference value of image, leads under backlight scene office in image
Portion's overexposure or part are excessively dark.How under backlight scene, it is effectively improved and is reappeared the key feature information for capturing image, is become
Current intelligent transportation system and field of image processing extreme stubborn problem.
In order to improve the road vehicle under backlight scene capture image effect, traditional Main there are several types of:
Method one, modification automation spectrum assignment strategy, that is, increase imaging aperture time or improve imaging gain parameter,
So that the mistake dark areas details under backlighting condition shows.This method realizes that simply easy to operate, main problem is to aggravate
The loss of high bright part details, causes effective imaging region imperfect in image frame.In addition, shooting high speed moving vehicle,
Increase aperture time will lead to motion blur, excessively improve gain also can enlarged drawing noise, influence visual effect.
Method two increases light filling equipment, i.e., increasing imaging sensitivity, this method need candid camera and light filling equipment
It is effectively synchronous, improve hardware cost and system control complexity.
Method three, using the video camera for synthesizing function with high frame per second and with wide dynamic, this method mainly passes through
The mode of high dynamic range images (High-Dynamic Range, HDR) increases the dynamic range of image, high frame per second instantaneous exposure
It is imaged and multiframe synthesizes final image, reduced bright and cross dark areas, dynamic range is limited, can not fully meet various multiple
Miscellaneous backlight environment, under some special occasions, often effect is not clearly as camera Costco Wholesale valuableness causes very
Hardly possible is universal.
Method four, the method based on image signal process realize that the image gray-scale level reduction in backlight region, such as curve are drawn
Stretch, grayscale is balanced and color space conversion etc., this method is Global treatment mostly, causes image hierarchy sense not strong.
Summary of the invention
It is an object of the invention to improve above-mentioned conventional method deficiency present in practical implementation, propose that one kind mentions
The method and device of high backlight scene vehicle snapshot picture quality, mainly according to image local feature information self-adapting part increases
Candid photograph effect under strong backlighting condition realizes that simply adaptivity is strong, improves and capture the general of image processing method under backlight scene
Adaptive and validity.
The present invention is achieved by the following technical solutions:
The present invention provides a kind of methods for improving backlight scene vehicle snapshot picture quality, comprising the following steps:
Step S1: data after the initial data and processing of capturing frame image are obtained:
Step S101: the yuv format data flow of video image to be processed is obtained using image capture module, is currently grabbed
The YUV image data of frame are clapped, Y-component image, U component image and the V component image of YUV image data are obtained;
Step S102: the YUV image data of step S101 are converted into rgb image data, calculate the R of rgb image data
The corresponding component image of maximum value is labeled as lightness component figure by the maximum value of component image, G component image, B component image
Picture is denoted as V';
Step S103: calculating the whole mean value Ymean of the Y-component image of step S101, according to the whole equal of Y-component image
Value divides the brightness degree coefficient Ygrade of Y-component image;
Step S104: being smoothed the Y-component image of step S101, and calculates filtering as a result, obtaining
Yfilter component image;
Step S2: backlight compensation treated luminance component image is calculated:
Step S201: building brightness mapping curve:
Wherein, variable x indicates input signal, and x is the numerical value after normalized, and range is 0~1;Variable y is indicated
Mapping curve output valve, range are 0~1;Variable ctrl_y is the amplitude control parameter of mapping curve, the characteristic having are as follows:
Different ctrl_y numerical value have different response curves, and ctrl_y numerical value is smaller, and the promotion amplitude of mapping curve is bigger;Conversely, mapping
The promotion amplitude of curve is smaller;
Step S202: the Yfilter component image of step S104 is normalized, the brightness of step S201 is utilized
Mapping curve calculates output valve and by output valve multiplied by image gray-scale level maximum value, is as a result expressed as Ymp;Image gray-scale level herein is most
Big value is determined by picture depth, if image is N bit depth image, then image gray-scale level maximum value is 2N-1;
Step S203: calculating the mapping result of the V' component image of step S102, obtains Vmp component image:
Step S204: carrying out proportion weighted fusion for Y-component image and Vmp component image, will merge by proportion weighted
Data afterwards are denoted as Yout as the final luminance component image for capturing frame image;
Step S3: backlight compensation treated color component images are calculated:
Due to carrying out backlight processing to luminance Y component, i.e., the dark of image reversible-light shooting is had adjusted using grayscale mapping curve
Area improves the visual effect of dark space, but also causes the color saturation of image to change with bright-colored degree simultaneously, institute
To need to correct color component in conjunction with the backlight degree for the treatment of of luminance Y component, specifically:
Backlight processing is carried out to U component image and V component image, processing result is obtained and is expressed as Uout and Vout:
In formula, ctrl_uv indicates the control intensity of color component;
Step S4: output by backlight compensation treated capture frame YUV image data: by Yout component image, Uout
Component image and Vout component image are as the final YUV image output for capturing frame.
Further, in the step S103, the entirety of Y-component image is calculated using the method for point traversal statistics pixel-by-pixel
Mean value Ymean.
Further, in the step S104, Y-component image is smoothed using two-dimensional convolution filter, then
Gaussian filter or mean filter is selected to calculate filtering as a result, obtaining Yfilter component image.
Further, in the step S201, ctrl_y numerical value is determined according to brightness degree coefficient Ygrade, brightness degree
Coefficient is bigger, and ctrl_y value is bigger.
Further, in the step S204, the weighting coefficient of proportion weighted fusion passes through the grayscale of respective components image
Range carries out value, if the index variables of component image grayscale are i, in Y-component image and Vmp component image, grayscale i is corresponding
Weighting coefficient be Wy (i) and Wv (i), in which:
Wy (i)=1-Wv (i)
In formula, threshold value La and threshold value Lb are the control parameters of respective components image gray-scale level Weighted Fusion.Parameter, Δ w expression pair
Answer the datum quantity of component image weighting coefficient.
Further, in the step S3, ctrl_uv numerical value carries out value according to brightness degree coefficient Ygrade.
The present invention also provides the devices that backlight scene vehicle snapshot picture quality is improved using the above method, including image
Acquisition module, image backlight compensation processing module and image display, in which:
Described image acquisition module is used to acquire the yuv format data flow diagram picture of moving target (vehicle), and will currently grab
The YUV image data for clapping frame are sent to image backlight compensation processing module;
The method that described image backlight compensation processing module uses above-mentioned raising backlight scene vehicle snapshot picture quality, will
The current YUV image data for capturing frame carry out backlight compensation processing, the YUV image number for the backlight compensation enhancing that obtains that treated
According to being then forwarded to image display;
Treated for showing backlight compensation captures image for described image display module.
The present invention has the advantage that the present invention provides a kind of raising backlight scene vehicle snapshot figures compared with prior art
The method and device of image quality amount, this method enhance the candid photograph effect of backlight scene according to image local feature information self-adapting,
While promoting backlight dark picture areas details, it can preferably retain highlighted details and Image Warping.In engineer application
It is upper to realize that simply adaptivity is strong, improves traffic route video camera and captures the pervasive of image processing method under backlight scene
Property and validity.
Detailed description of the invention
Fig. 1 is the step flow chart for improving the method for backlight scene vehicle snapshot picture quality;
Fig. 2 is the step flow chart of data after obtaining raw image data and processing;
Fig. 3 is the step flow chart for calculating backlight compensation treated luminance component image;
Fig. 4 is the structural schematic diagram for improving the device of backlight scene vehicle snapshot picture quality.
Specific embodiment
It elaborates below to the embodiment of the present invention, the present embodiment carries out under the premise of the technical scheme of the present invention
Implement, the detailed implementation method and specific operation process are given, but protection scope of the present invention is not limited to following implementation
Example.
Embodiment 1
A kind of method and apparatus for improving backlight scene vehicle snapshot picture quality are present embodiments provided, such as Fig. 1-3 institute
Show, the method step includes:
Step S1: data after the initial data and processing of capturing frame image are obtained:
Step S101: the yuv format data flow of video image to be processed is obtained using image capture module, is currently grabbed
The YUV image data of frame are clapped, Y-component image, U component image and the V component image of YUV image data are obtained;
In the present embodiment, the YUV image data of candid photograph are 8bit depth image, and the YUV image data deposit after candid photograph is slow
Deposit operation interval.
Step S102: the YUV image data of step S101 are converted to RGB image by designed image color space converter
Data, and it is stored in caching operation interval, the matrix coefficient configuration of color of image space convertor is as follows:
Since YUV image data are 8bit, the rgb image data after converting is also into 8bit.
Rgb image data is read from caching operation interval, calculates the maximum of R component image, G component image, B component image
Value, and component corresponding to maximum value is labeled as lightness component image V', it may be assumed that
V'=max (R, G, B)
For 8bit depth image, the value range of V' is 0~255, and V' component image is stored in caching operation interval.
Step S103: reading Y-component image from caching operation interval, by the way of point traversal statistics pixel-by-pixel, calculates Y
The whole mean value of component image is labeled as Ymean.Since YUV image is 8bit depth image, the value range of Ymean
It is 0~225.The brightness degree coefficient Ygrade of Y-component image is divided according to the whole mean value of Y-component image:
When the value range of Ymean is 0~16 section, brightness degree coefficient Ygrade value 0;
When the value range of Ymean is 17~64 section, brightness degree coefficient Ygrade value 1;
When the value range of Ymean is 64~90 section, brightness degree coefficient Ygrade value 2;
When the value range of Ymean is 91~255 section, brightness degree coefficient Ygrade value 3.
Step S104: reading Y-component image from caching workspace, is carried out using two-dimensional convolution filter to Y-component image
Smoothing processing, then calculate filtering result.In order to introduce the spatial neighborhood relationship of image pixel, reach realization to Y component map
The purpose of the smooth effect of picture can select Gaussian filter or mean filter to be filtered the calculating of sharpening result.This
In embodiment, the two-dimentional mean filter of 3 × 3 Size of Neighborhood is selected to calculate the filtering of Y-component image as a result, and will put down
Slipped Clove Hitch fruit is expressed as Yfilter.Filtering result Yfilter is finally deposited into caching operation interval.
Step S2: backlight compensation treated luminance component image is calculated:
Step S201: building brightness mapping curve:
Wherein, variable x indicates input signal, and x is the numerical value after normalized, and range is 0~1;Variable y is indicated
Mapping curve output valve, range are 0~1;Variable ctrl_y is the amplitude control parameter of mapping curve, the characteristic having are as follows:
Different ctrl_y numerical value have different response curves, and ctrl_y numerical value is smaller, and the promotion amplitude of mapping curve is bigger;Conversely, mapping
The promotion amplitude of curve is smaller.
In the present embodiment, the value of ctrl_y numerical value is determined according to the brightness degree coefficient Ygrade for capturing frame image,
Range intervals are 0.1~2.0:
When current brightness level coefficient Ygrade value 0, ctrl_y value range is 0.1~0.2;
When current brightness level coefficient Ygrade value 1, ctrl_y value range is 0.2~0.5;
When current brightness level coefficient Ygrade value 2, ctrl_y value range is 0.5~1.0;
When current brightness level coefficient Ygrade value 3, ctrl_y value range is 1.0~2.0.
Step S202: the Yfilter component image of step S104 is normalized, the brightness of step S201 is utilized
Mapping curve calculates output valve and by output valve multiplied by image gray-scale level maximum value, and result is expressed as Ymp;The image of the present embodiment
For 8bit depth image, corresponding grayscale maximum value is 255;
Step S203: carrying out mapping processing to the V' component image of step S102, obtains Vmp component image, and is stored in slow
Deposit operation interval:
Step S204: Y-component image and Vmp component image are subjected to proportion weighted fusion:
Yout=Y*Wy+Vmp*Wv
In formula, Wy is the weighting coefficient of Y-component image, and value range is the weighting system that 0~1, Wv is Vmp component image
Number, value range are 0~1, and Wy+Wv=1, as long as so determine Wy and Wv parameter one of those.Due to Y-component and
Vmp component is 8bit data, and grey-scale range is 0~255.So weighting coefficient (Wy and Wv) can be according to different grey-scale ranges
Value.
In the present embodiment, it is assumed that index variables of the grayscale between range 0~255 are i, then ash inside Vmp component image
Corresponding weighting coefficient Wv (i) calculating formula of rank i is as follows:
In formula, parameter i indicates the index value of 8bit image gray-scale level, value range 0~255;Threshold value La and threshold value Lb is figure
As the control parameter of grayscale Weighted Fusion, threshold value La value range 0~64, threshold value Lb value range 192~255;Parameter, Δ w table
Show the datum quantity of weighting coefficient, value range 0~0.2.
After aforesaid operations, Y-component and Vmp component can be subjected to proportion weighted fusion, and obtain final brightness point
Amount is expressed as Yout, and Yout is then deposited into caching operation interval.
Step S3: backlight compensation treated color component images are calculated:
The color component for capturing frame image is read from caching operation interval, color component includes U component image and V
Component image.Due to carrying out backlight processing to luminance Y component, i.e., the dark of image reversible-light shooting is had adjusted using grayscale mapping curve
Area, improves the visual effect of dark space, and the color saturation of image is also caused to change with bright-colored degree.So needing
Color component is corrected in conjunction with the backlight degree for the treatment of of luminance Y component.
Here, to color component: the backlight treatment process of U component image and V component image is as follows:
Ctrl_uv indicates the control intensity of color component, as follows according to brightness degree coefficient Ygrade value:
When value 0 or 1 current brightness level coefficient Ygrade, ctrl_uv value range is 1.0~1.2;
When value 2 or 3 current brightness level coefficient Ygrade, ctrl_uv value 1.0.
The backlight of U component and V component processing output result Uout component and Vout component are deposited into caching operation interval.
Step S4: Yout component, Uout component and Vout component are read from caching operation interval, as final candid photograph frame
The output of image backlight processing result.
The present embodiment additionally provides the device that backlight scene vehicle snapshot picture quality is improved using the above method, has such as
Structure shown in Fig. 4, including image capture module, image backlight compensation processing module and image display, in which:
Described image acquisition module is used to acquire the yuv format data flow diagram picture of moving target, and will currently capture frame
YUV image data are sent to image backlight compensation processing module;
The method that described image backlight compensation processing module uses above-mentioned raising backlight scene vehicle snapshot picture quality, will
The current YUV image data for capturing frame carry out backlight compensation processing, the YUV image number for the backlight compensation enhancing that obtains that treated
According to being then forwarded to image display;
Treated for showing backlight compensation captures image for described image display module.
The above are a kind of detailed embodiment and specific operating process of the present invention, are before being with technical solution of the present invention
It puts and is implemented, but protection scope of the present invention is not limited to the above embodiments.
Claims (2)
1. a kind of method for improving backlight scene vehicle snapshot picture quality, which comprises the following steps:
Step S1: data after the initial data and processing of capturing frame image are obtained:
Step S101: obtaining the yuv format data flow of video image to be processed using image capture module, obtains currently capturing frame
YUV image data, obtain YUV image data Y-component image, U component image and V component image;
Step S102: the YUV image data of step S101 are converted into rgb image data, calculate the R component of rgb image data
The corresponding component image of maximum value is labeled as lightness component image, note by the maximum value of image, G component image, B component image
For V';
Step S103: calculating the whole mean value Ymean of the Y-component image of step S101, is drawn according to the whole mean value of Y-component image
Divide the brightness degree coefficient Ygrade of Y-component image, the method calculating Y component map counted in this step using point traversal pixel-by-pixel
The whole mean value Ymean of picture;
Step S104: being smoothed the Y-component image of step S101, and calculates filtering as a result, obtaining Yfilter
Component image is smoothed Y-component image using two-dimensional convolution filter in this step, then select Gaussian filter or
Mean filter calculates filtering as a result, obtaining Yfilter component image;
Step S2: backlight compensation treated luminance component image is calculated:
Step S201: building brightness mapping curve:
Wherein, variable x indicates input signal, and x is the numerical value after normalized, and range is 0~1;Variable y indicates mapping
Curve output valve, range are 0~1;Variable ctrl_y is the amplitude control parameter of mapping curve, ctrl_y numerical value root in this step
Determine that brightness degree coefficient is bigger, and ctrl_y value is bigger according to brightness degree coefficient Ygrade;
Step S202: the Yfilter component image of step S104 is normalized, and is mapped using the brightness of step S201
Curve calculates output valve and by output valve multiplied by image gray-scale level maximum value, is as a result expressed as Ymp;
Step S203: calculating the mapping result of the V' component image of step S102, obtains Vmp component image:
Step S204: carrying out proportion weighted fusion for Y-component image and Vmp component image, will be fused by proportion weighted
Data are denoted as Yout as the final luminance component image for capturing frame image, and the weighting coefficient of proportion weighted fusion passes through correspondence
The grey-scale range of component image carries out value, if the index variables of component image grayscale are i, in Y-component image and Vmp component map
As in, the corresponding weighting coefficient of grayscale i is Wy (i) and Wv (i), in which:
Wy (i)=1-Wv (i)
In formula, threshold value La and threshold value Lb are the control parameters of respective components image gray-scale level Weighted Fusion, and parameter, Δ w indicates corresponding point
Datum quantity of the spirogram as weighting coefficient;
Step S3: backlight compensation treated color component images are calculated:
Backlight processing is carried out to U component image and V component image, processing result is obtained and is expressed as Uout and Vout:
In formula, ctrl_uv indicates the control intensity of color component, according to brightness degree coefficient Ygrade value;
Step S4: output by backlight compensation treated capture frame YUV image data: by Yout component image, Uout component
Image and Vout component image are as the final YUV image output for capturing frame.
2. a kind of device for improving backlight scene vehicle snapshot picture quality using method as described in claim 1, including image
Acquisition module, image backlight compensation processing module and image display, it is characterised in that:
Described image acquisition module is used to acquire the yuv format data flow diagram picture of moving target, and the current YUV for capturing frame is schemed
As data are sent to image backlight compensation processing module;
The method that described image backlight compensation processing module uses above-mentioned raising backlight scene vehicle snapshot picture quality, will be current
The YUV image data for capturing frame carry out backlight compensation processing, obtain the YUV image data of treated backlight compensation enhancing, then
It is sent to image display;
Treated for showing backlight compensation captures image for described image display module.
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CN103002291A (en) * | 2012-12-06 | 2013-03-27 | 杭州藏愚科技有限公司 | Camera wide dynamic image enhancement method and device |
CN106023117A (en) * | 2016-06-01 | 2016-10-12 | 哈尔滨工业大学(威海) | Backlight image recovery method based on nonlinear brightness enhancement model |
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