CN104463812B - The method for repairing the video image by raindrop interference when shooting - Google Patents
The method for repairing the video image by raindrop interference when shooting Download PDFInfo
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Abstract
A kind of method for the video image repaired and interfered when shooting by raindrop is provided.The method includes：(A) a frame image of the video based on rgb color space is received；(B) the frame image received is converted into the image based on HSL color spaces；(C) based in chrominance component and the transformed image of saturation degree component detection pure raindrop part and raindrop and moving object lap；(D) it is based on luminance component and raindrop removal is carried out to pure raindrop part and raindrop and moving object lap respectively；(E) image after removal raindrop is converted into the image based on rgb color space and output.According to the method, the precision and efficiency of restored video image can be improved under the premise of high robust.
Description
Technical field
The present invention relates to technical field of image processing, more particularly, it is dry by raindrop when shooting to be related to a kind of reparation
The method for the video image disturbed.
Background technology
Rain has a great impact to image imaging, image blur, information can be caused capped so that video image
Clarity declines, the digitized processing performance of video image declines.Therefore, to shooting when by raindrop interference video image into
Row repair process is conducive to being further processed for image, including improve target detection based on image, identification, tracking, segmentation and
The performance of the technologies such as monitoring.Video image goes rain technology has widely in fields such as modern military, traffic and security monitorings
Application prospect.
The existing rain algorithm for video image, applies more mature on the video image of static scene, but answers
With being unable to reach ideal detection result on the video image of dynamic scene.
In addition, in real time to shooting when by raindrop interference video image carry out repair process automated navigation system, peace
There is prodigious demand in the occasions such as full monitoring system.It generally requires to obtain handling result in time in these application scenarios, feed back to
User, the lag of video processing are likely to result in user and do the judgement to make mistake.And existing the rain is gone to calculate for video image
Since complexity of its calculating causes less efficient, real-time need to be improved method.
Invention content
Exemplary embodiment of the present invention is to provide a kind of video image repaired and interfered when shooting by raindrop
Method, to overcome the problems, such as that reparation precision and remediation efficiency are undesirable in the prior art.
The present invention provides a kind of method for the video image repaired and interfered when shooting by raindrop, which is characterized in that packet
It includes：(A) a frame image of the video based on rgb color space is received；(B) the frame image received is converted into being based on HSL
The image of color space；(C) based in chrominance component and the transformed image of saturation degree component detection pure raindrop part and
Raindrop and moving object lap；(D) luminance component is based on respectively to be overlapped pure raindrop part and raindrop and moving object
Part carries out raindrop removal；(E) image after removal raindrop is converted into the image based on rgb color space and output.
Optionally, step (C) includes：(C1) it is based in transformed image described in chrominance component and saturation degree component detection
Moving object part；(C2) according to gray scale difference, the rain of the frame image and a frame image adjacent with the frame image
The optical characteristics and chromatic characteristic of drop detect in the transformed image is polluted part by raindrop；(C3) by the moving object
Body portion and the lap that part is polluted by raindrop are determined as raindrop and moving object lap, and will be described by rain
Part in drop pollution part in addition to partly overlapping with the moving object is determined as pure raindrop part.
Optionally, step (C1) includes：(C11) it is based on transformed image described in chrominance component and saturation degree component detection
In moving object edge；(C12) pixel in the transformed image is clustered according to color character, it will
The transformed image segmentation is at multiple pieces；(C13) by the pixel inside the block belonging to the edge of the moving object detected
Point is labeled as the pixel for belonging to moving object part.
Optionally, step (C11) includes：Make a reservation for when the metric function value of the pixel in the transformed image is more than
When threshold value, determine that the pixel is located on the edge of moving object, wherein metric function F (x, y) is：
Wherein, Hr(x, y) indicates the tone value of pixel (x, y), Hb(x, y) indicates the background color tone of pixel (x, y)
Value, Sr(x, y) indicates the intensity value of pixel (x, y), Sb(x, y) indicates the background intensity value of pixel (x, y),Indicate the gray value of pixel (x, y),Indicate the background gray levels of pixel (x, y).
Optionally, step (D) includes：The brightness value of each pixel in pure raindrop part is replaced with：One frame
The weighted average of the brightness value of corresponding pixel points in the preceding M frames image to rear M frames image of image, wherein M is more than 0
Integer；The brightness value of each pixel in raindrop and moving object lap is replaced with：The one frame image it is previous
The brightness value of the neighbor pixel of the corresponding pixel points and corresponding pixel points in each frame image in frame image to a later frame image
Weighted average average value.
Optionally, M=3, wherein the brightness value of the pixel (x, y) in pure raindrop part, which is calculate by the following formula, to be replaced
Change value：
Wherein, N is the frame number of the frame image, and L (x, y, t) indicates the brightness of the pixel (x, y) of t frame images
Value, Fb(t) it is weighting coefficient matrix, Fb(t)[1,2,4,0,4,2,1]。
Optionally, the brightness value of the pixel (x, y) in raindrop and moving object lap is calculate by the following formula to obtain
Replacement values：
Wherein, N is the frame number of the frame image, and L (x, y, t) indicates the brightness of the pixel (x, y) of t frame images
Value, V indicate pixel corresponding with pixel (x, y) in the previous frame image to a later frame image of the frame image and right
The domain that the neighbor pixel for the pixel answered is constituted, Fm(x, y, t) is weighting coefficient matrix,
Reparation according to an exemplary embodiment of the present invention by the method for the video image of raindrop interference, is based on when shooting
It the HSL color spaces of video image and the identification of moving target is realized improves restored video image under the premise of high robust
Precision and efficiency.
It will illustrate the other aspect and/or advantage of present general inventive concept in part in following description, also one
Divide and will be apparent by description, or can be learnt by the implementation of present general inventive concept.
Description of the drawings
Fig. 1 shows the side of the video image according to an exemplary embodiment of the present invention repaired and interfered when shooting by raindrop
The flow chart of method；
Fig. 2 shows the flow charts of the method for detection moving object part according to an exemplary embodiment of the present invention.
Specific implementation mode
The embodiment of the present invention is reference will now be made in detail, examples of the embodiments are shown in the accompanying drawings, wherein identical mark
Number identical component is referred to always.It will illustrate the embodiment by referring to accompanying drawing below, to explain the present invention.
Fig. 1 shows the side of the video image according to an exemplary embodiment of the present invention repaired and interfered when shooting by raindrop
The flow chart of method.
Referring to Fig.1, in step S10, a frame image of the video based on rgb color space is received.
In step S20, the frame image received is converted into the image based on HSL color spaces.
Particularly, by red (R) component based on rgb color space received, green (G) component and blue (B)
The RGB image of representation in components is converted into based on tone (H) component, saturation degree (S) component and the brightness (L) in HSL color spaces
The image of representation in components, to carry out the detection and removal of raindrop under HSL color spaces.
The image based on rgb color space can be converted into the image based on HSL color spaces by following formula：
Wherein, max indicates that the maximum value in R, G, B component, min indicate the minimum value in R, G, B component.
It is unrelated with the tonal properties of raindrop and saturation degree characteristic since removal raindrop are related with the light characteristic of raindrop, because
This, the image based on HSL color spaces is converted by RGB image, so that it may raindrop removal is carried out only for the luminance component of raindrop,
And the detection that moving target can be carried out based on chrominance component and saturation degree component is carried to substantially reduce the complexity of algorithm
Computationally efficient.
In step S30, based in chrominance component and the transformed image of saturation degree component detection pure raindrop part and
Raindrop and moving object lap.
In one example, the moving object that can be primarily based in chrominance component and the transformed image of saturation degree component detection
Body portion.Here, it can be used various suitable methods based in chrominance component and the transformed image of saturation degree component detection
Moving object part.Preferably, it can be realized by the method for detection moving object part shown in Fig. 2.
Then, according to the gray scale difference of the frame image and a frame image adjacent with the frame image, the light of raindrop
It learns characteristic and chromatic characteristic detects in the transformed image and polluted part by raindrop.
In one example, gray scale difference of each pixel in two continuous frames video image can be acquired first, when a pixel
When the gray scale difference of point is more than difference threshold, it is determined that the pixel is the pixel of candidate polluted by raindrop.Here, difference threshold
The selection of value size will make the variation of the gray value of all pixels polluted by raindrop that can be detected.For example,
Difference threshold size can be taken as 3/255.
Then, the optics based on raindrop and chromatic characteristic further sieve the candidate pixel by raindrop pollution
Choosing, obtains the pixel polluted by raindrop, so that it is determined that being polluted part by raindrop.These characteristics include：Strength fluctuation range α,
The changing value etc. of largest connected region area β and rgb color component.For example, by the value of α between 3/255-30/255, β's
For value between 30-50 pixel, Δ R, Δ G and the approximately equal pixels of Δ B are determined as the pixel polluted by raindrop, no
Then it is determined as the non-pixel polluted by raindrop.Here, the value of α and β can according to the size of raindrop, the size of video frame and
Shooting focal length etc. is configured.
The moving object part and the lap that part is polluted by raindrop are determined as raindrop and moving object
Lap, in the moving object part except with it is described partly overlapped by raindrop pollution in addition to part be determined as pure moving object
Body portion, and the part polluted in part in addition to partly overlapping with the moving object by raindrop is determined as pure raindrop
Part, to detect pure raindrop part, raindrop and moving object lap, pure moving object part.
In other words, their intersection is obtained as raindrop and moving object in conjunction with moving object part and by raindrop pollution part
Body lap, part of the moving object part in addition to the intersection are pure moving object part, and being removed by raindrop pollution part should
Part except intersection is pure raindrop part.
It should be appreciated that, it is possible to use other suitable methods are based on chrominance component and the transformed figure of saturation degree component detection
Pure raindrop part and raindrop as in and moving object lap.
In step S40, pure raindrop part and raindrop and moving object lap are carried out respectively based on luminance component
Raindrop remove.
Since pure moving object part is not polluted by raindrop, brightness value remains unchanged, and therefore, only need to be based on brightness
Component carries out raindrop removal to pure raindrop part and raindrop and moving object lap respectively.
In one example, the brightness value of each pixel in pure raindrop part can be replaced with：The one frame image
Preceding M frames image to rear M frames image in corresponding pixel points brightness value weighted average, wherein M is integer more than 0.
That is, pure raindrop part can be replaced by the weighted average of the brightness value of the pixel in the front and back M frames in time domain space
In the pixel brightness value.
The brightness value of each pixel in raindrop and moving object lap is replaced with：Before the one frame image
The brightness of the neighbor pixel of the corresponding pixel points and corresponding pixel points in each frame image in one frame image to a later frame image
The average value of the weighted average of value.For the brightness value of the pixel in raindrop and moving object lap, due to frame it
Between relativity of time domain and little, spatial coherence bigger, is averaged so can only choose front and back each frame in time domain instead,
And carry out the weighted average of the pixel and the neighbor pixel of the pixel in each frame respectively, to comprehensive temporal and spatial correlations
Property carry out raindrop removal.
For example, M=3, wherein the brightness value of the pixel (x, y) in pure raindrop part, which can be calculate by the following formula, to be replaced
Change value：
Wherein, N is the frame number of the frame image, and L (x, y, t) indicates the brightness of the pixel (x, y) of t frame images
Value, Fb(t) it is weighting coefficient matrix, Fb(t)[1,2,4,0,4,2,1]。
The brightness value of pixel (x, y) in raindrop and moving object lap, which can be calculate by the following formula, to be replaced
Value：
In step S50, the image after removal raindrop is converted into the image based on rgb color space and output.That is, by complete
The HSL images reconvert of Cheng Quyu processing is at RGB image to export.
Fig. 2 shows the flow charts of the method for detection moving object part according to an exemplary embodiment of the present invention.It can hold
It is executed when row step S30.
As shown in Fig. 2, in step S301, based in transformed image described in chrominance component and saturation degree component detection
The edge of moving object.
Since raindrop falling speed is very fast, spherical raindrop are not observed substantially under normal exposure speed, on image, and
It is that raindrop are formed by rain line due to quickly moving.In a natural environment, formula (6) can describe the physics imaging process of raindrop, and
It can quantitatively describe to generate when raindrop fall fuzzy：
Ir(x,y)αIE(x,y)+(1-α)Ib(x,y) (6)
Wherein, Ir(x, y) indicates the gray value of pixel (x, y), IE(x, y) is indicated in time for exposure T, it is assumed that raindrop
It is covered in pixel (x, y) always and is formed by equivalent desired gray level value, Ib(x, y) indicates the background gray scale of pixel (x, y)
Value, that is, gray value when not polluted by raindrop, α τ/T indicate that time and exposure needed for pixel (x, y) are passed through in raindrop whereabouts
Ratio between light time.
Available light is to be mixed by the light of different frequency, therefore the optical model of raindrop imaging is based on any face
It is still set up in the channel of colouring component.That is, in formula (6) each variable with its after the representation in components in tri- channels R, G, B still
It sets up.It is with vector representation by three components：
Wherein, Rr(x, y) indicates the R component value of pixel (x, y), Gr(x, y) indicates the G component values of pixel (x, y),
Br(x, y) indicates the B component value of pixel (x, y), Rb(x, y) indicate pixel (x, y) background R component value (that is, not by
R component value when raindrop pollute), Gb(x, y) indicates the background G component values of pixel (x, y) (that is, when not polluted by raindrop
G component values), Bb(x, y) indicates the background B component value (that is, B component value when not polluted by raindrop) of pixel (x, y).
Since raindrop falling speed is very fast, so α τ/T level off to zero, α/(1- α) and level off to zero, by formula (1), formula (2),
Formula (3) and formula (8) joint it is found that by raindrop pollution pixel in, Hr-HbAnd Sr-SbApproach zero, i.e., by raindrop pollution
Tone value (that is, background colour tone pitch) when the tone value and intensity value of pixel are not polluted by raindrop with the pixel and satisfy
It is smaller that variation is compared with angle value (that is, background intensity value).And for the pixel on the edge of moving object, tone value
Obvious variation can occur with intensity value.
Since the tone value of the pixel polluted by raindrop changes smaller, and the side of moving object compared with background colour tone pitch
The tone value of pixel on edge changes greatly.But the blurring effect due to being formed by different video quality and distant view misty rain
It influences, the tone value and background colour tone pitch of the pixel accurately polluted by raindrop, therefore single use tone value can not be obtained
The edge that can not accurately detect moving object needs to construct metric function in conjunction with intensity value and gray value.
Therefore, can construct metric function F (x, y) is：
Wherein, Hr(x, y) indicates the tone value of pixel (x, y), Hb(x, y) indicates the background color tone of pixel (x, y)
Value, Sr(x, y) indicates the intensity value of pixel (x, y), Sb(x, y) indicates the background intensity value of pixel (x, y),Indicate the gray value of pixel (x, y),Indicate the background gray levels of pixel (x, y).
It should be understood that the consecutive frame that the background colour tone pitch of pixel (x, y) can not polluted by raindrop by the pixel
In the pixel tone value obtain, the background intensity value and background gray levels of pixel can also be obtained by corresponding mode
.
Due to the chromatic characteristic of raindrop, zero is leveled off to by the metric function value of the pixel of raindrop pollution, and moving object
Edge on pixel obvious variation can all occur due to tone value and intensity value, metric function value is one
A bigger value.Therefore, the pixel on edge of the threshold value to filter out moving object can be set.I.e. when the conversion
When the metric function value of the pixel in image afterwards is more than predetermined threshold, determine that the pixel is located at the edge of moving object
On.
In step S302, the pixel in the transformed image is clustered according to color character, it will be described
Transformed image segmentation is at multiple pieces.
In step S303, the pixel inside the block belonging to the edge of the moving object detected is labeled as to belong to movement
The pixel of object parts.That is, determining moving object part using color clustering image partition method.
In addition, the above method of exemplary embodiment according to the present invention may be implemented as computer program, to work as
When running the program, the above method is realized.
Reparation according to an exemplary embodiment of the present invention by the method for the video image of raindrop interference, is based on when shooting
It the HSL color spaces of video image and the identification of moving target is realized improves restored video image under the premise of high robust
Precision and efficiency.
Although having show and described some exemplary embodiments of the present invention, it will be understood by those skilled in the art that
It, can be to these in the case where not departing from the principle and spirit of the invention defined by the claims and their equivalents
Embodiment is modified.
Claims (4)
1. a kind of reparation is when shooting by the method for the video image of raindrop interference, which is characterized in that including：
(A) a frame image of the video based on rgb color space is received；
(B) the frame image received is converted into the image based on HSL color spaces；
(C) based in chrominance component and the transformed image of saturation degree component detection pure raindrop part and raindrop and moving object
Body lap；
(C1) based on the moving object part in transformed image described in chrominance component and saturation degree component detection；
Step (C11) includes：
(C11) edge based on the moving object in transformed image described in chrominance component and saturation degree component detection；Work as institute
When stating the metric function value of the pixel in transformed image more than predetermined threshold, determine that the pixel is located at moving object
On edge,
Wherein, metric function F (x, y) is：
Wherein, Hr(x, y) indicates the tone value of pixel (x, y), Hb(x, y) indicates the background colour tone pitch of pixel (x, y), Sr
(x, y) indicates the intensity value of pixel (x, y), Sb(x, y) indicates the background intensity value of pixel (x, y),Refer to
Show the gray value of pixel (x, y),Indicate the background gray levels of pixel (x, y)；
(C12) pixel in the transformed image is clustered according to color character, by the transformed figure
As being divided into multiple pieces；
(C13) pixel inside the block belonging to the edge of the moving object detected is labeled as belonging to moving object part
Pixel；
(C2) according to the optical characteristics of the gray scale difference of the frame image and a frame image adjacent with the frame image, raindrop
It is detected in the transformed image with chromatic characteristic and is polluted part by raindrop；
When the gray scale difference is more than difference threshold, it is determined that be the image of candidate polluted by raindrop, the difference threshold is big
It is small to be taken as 3/255；
The optical characteristics and chromatic characteristic of the raindrop include：Strength fluctuation range α and largest connected region area β, by the value of α
Between 3/255-30/255, the value of β is between 30-50 pixel；
(C3) the moving object part and the lap that part is polluted by raindrop are determined as raindrop and moving object
Lap, in the moving object part except with it is described partly overlapped by raindrop pollution in addition to part be determined as pure moving object
Body portion, and the part polluted in part in addition to partly overlapping with the moving object by raindrop is determined as pure raindrop
Part；
(D) it is based on luminance component and raindrop removal is carried out to pure raindrop part and raindrop and moving object lap respectively；
(E) image after removal raindrop is converted into the image based on rgb color space and output.
2. the method as described in claim 1, which is characterized in that step (D) includes：
The brightness value of each pixel in pure raindrop part is replaced with：The preceding M frames image of the one frame image is to rear M frames figure
The weighted average of the brightness value of corresponding pixel points as in, wherein M is the integer more than 0；
The brightness value of each pixel in raindrop and moving object lap is replaced with：The former frame of the one frame image
The brightness value of the neighbor pixel of the corresponding pixel points and corresponding pixel points in each frame image in image to a later frame image
The average value of weighted average.
3. method as claimed in claim 2, which is characterized in that M=3,
Wherein, the brightness value of the pixel (x, y) in pure raindrop part is calculate by the following formula to obtain replacement values：
Wherein, N is the frame number of the frame image, and L (x, y, t) indicates the brightness value of the pixel (x, y) of t frame images, Fb
(t) it is weighting coefficient matrix, Fb(t)=[1,2,4,0,4,2,1].
4. method as claimed in claim 2, which is characterized in that the pixel (x, y) in raindrop and moving object lap
Brightness value be calculate by the following formula to obtain replacement values：
Wherein, N is the frame number of the frame image, and L (x, y, t) indicates the bright of the pixel (x, y) of t frame images
Angle value, V indicate the corresponding picture with pixel (x, y) in the previous frame image to a later frame image of the frame image
The domain that the neighbor pixel of vegetarian refreshments and corresponding pixel is constituted, Fm(x, y, t) is weighting coefficient matrix,
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| CN106056545A (en) * | 2016-05-24 | 2016-10-26 | 中国科学院深圳先进技术研究院 | Image rain removing method and image rain removing system |
| WO2019041147A1 (en) * | 2017-08-29 | 2019-03-07 | 广东虚拟现实科技有限公司 | Spot recognition method, device and system |
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