CN102243758A - Fog-degraded image restoration and fusion based image defogging method - Google Patents

Fog-degraded image restoration and fusion based image defogging method Download PDF

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CN102243758A
CN102243758A CN2011101978003A CN201110197800A CN102243758A CN 102243758 A CN102243758 A CN 102243758A CN 2011101978003 A CN2011101978003 A CN 2011101978003A CN 201110197800 A CN201110197800 A CN 201110197800A CN 102243758 A CN102243758 A CN 102243758A
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陶叔银
冯华君
徐之海
李奇
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Zhejiang University ZJU
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Abstract

The invention discloses a fog-degraded image restoration and fusion based image defogging method. The method comprises the following steps: 1) inputting a visible image and a near-infrared image of a same foggy scene, and respectively carrying out weighted least-square filtering on the luminance information of the visible image and the near-infrared image many times, then obtaining the luminance information of a fused image according to the obtained filtering results; 2) replacing the luminance information of the original visible image with the obtained luminance information of the fused image so as to obtain a preliminary defogging result; 3) obtaining a dark channel of the fused visible image, then obtaining the atmospheric light value of the fused visible image according to the dark channel; 4) obtaining the initial transmittance value of the fused visible image according to dark channel prior, then optimizing the initial transmittance value according to a soft sectional drawing method so as to obtain an optimized transmittance; and 5) according to a fog-degraded image formation model, restoring the fused visible image by using the atmospheric light value and the optimized transmittance so as to obtain a final defogging image. The method disclosed by the invention has the advantages of improving the contrast ratio and sharpness of a fog-degraded image and increasing the details of the fog-degraded image.

Description

Image defogging method capable based on Misty Image recovery and image co-registration
Technical field
The present invention relates to image processing field, relate in particular to a kind of based on visible images and near-infrared image, in conjunction with the defogging method capable of dark primary priori and weighted least-squares wave filter.
Background technology
Under the greasy weather situation, because the visibility of scenery reduces, consequently in the image that camera obtains, target contrast and color characteristic are decayed widely, therefore need to eliminate the influence of fog.Along with the continuous development of computer technology, handle and become possibility there being scenery image under the mist condition to carry out mist elimination.In fact, the image mist elimination is the important content of computer vision field research always, and it is mainly used in fields such as target detection, video monitoring, topographic(al) reconnaissance and automatic driving.The method of image mist elimination mainly contains two classes at present, and promptly Misty Image strengthens and the Misty Image recovery.
The Enhancement Method of Misty Image is not considered the reason of image degradation, and list strengthens the contrast of image from the angle of Flame Image Process, improves the visual effect of image, the details of outstanding image, but may cause certain loss for the information of outshot; It is the physical process that the research Misty Image is degenerated that Misty Image is restored, and sets up degradation model, and the inverting degenerative process compensates because there is the image fault that is caused in fog, thereby improves the quality of Misty Image.This method is with strong points, and the mist elimination effect nature that obtains does not generally have information loss, and the key point of processing is the estimation of parameter in the model.
Image co-registration is meant that the view data of the same target that different-waveband is collected is through Flame Image Process and computer technology etc., extract the effective information in each band image to greatest extent, be fused into high-quality image at last, thereby improve the utilization factor of image information, the contrast of transparency information and target in the enhancing image is to form clarity, integrality and the accuracy that target information is described.Image co-registration fully realized at the application potential of aspects such as medical science, remote sensing, computer vision, weather forecast and military target identification, especially aspect the computer vision, image co-registration is considered to overcome the technique direction of some difficult point at present; On space flight, the multiple carrying platform of aviation, the fusion of a large amount of spectral remote sensing images that various remote sensor obtained for the high efficiency extraction of information provides good processing means, obtains obvious benefit.But, the image defogging method capable in conjunction with Misty Image recovery and image co-registration is not also proposed at present, the effect of traditional Misty Image defogging method capable is all not ideal enough.
Summary of the invention
The purpose of this invention is to provide clear picture behind a kind of mist elimination, contrast and sharpness height, details abundant restore image defogging method capable with image co-registration based on Misty Image.
For solving the problems of the technologies described above, the technical solution used in the present invention is: a kind of based on the image defogging method capable of Misty Image recovery with image co-registration, implementation step is as follows:
1) same visible images and the near-infrared image that the mist scene is arranged of input carries out multi-time weighted least squares filtering respectively with the monochrome information and the near-infrared image of visible images, obtains image luminance information through merging according to the filtering result;
2) with the monochrome information of the alternative former visible images of image luminance information after merging, obtain preliminary mist elimination result;
3) obtain the dark primary that merges visible images, and obtain the atmosphere light value that merges visible images according to dark primary;
4) obtain the transmissivity initial value that merges visible images according to dark primary priori, the transmissivity initial value is optimized the transmissivity after being optimized according to soft stingy drawing method;
5) form model according to mist figure, utilize the transmissivity after described atmosphere light value and the described optimization to recover described fusion visible images, obtain final mist elimination image.
As further improvement in the technical proposal of the present invention:
The image luminance information of carrying out multi-time weighted least squares filtering in the described step 1) and obtaining through merging according to the filtering result specifically is meant: the monochrome information or the near-infrared image of visible images are carried out the weighted least-squares filtering first time as input parameter, then current filtering result is carried out multi-time weighted least squares filtering as the input parameter of filtering next time, obtain the input parameter of filtering each time and output result's difference, and with this difference divided by output result when time filtering, obtain contrast images with corresponding many group visible images monochrome informations of filter times and near-infrared image; Each the group visible images monochrome information in described many group contrast images and the contrast images of near-infrared image are compared the higher value that obtains wherein, connect multiplication after then higher value being added 1, to connect the monochrome information that the multiplication result multiply by the visible images of last filtering output again, the image luminance information after obtaining merging.
When being weighted least squares filtering in the step 1), the expression formula of weighted least-squares filtering is Wherein Be the input parameter of the k time filtering, Z represents the monochrome information or the near-infrared image of the preliminary mist elimination image imported, Be the output parameter of the k time filtering and the input parameter of the k+1 time filtering,
Figure BDA0000075720090000024
Be the weighted least-squares wave filter.
Described weighted least-squares wave filter
Figure BDA0000075720090000025
Expression formula be
Figure BDA0000075720090000026
λ wherein 0c kBe the k time filtering result's roughness, λ 0The roughness of input parameter when carrying out filtering for the first time, c is a constant coefficient, k is the filtering sequence number, L gBe Laplce's matrix, U is and L gThe unit matrix of identical size.
Obtaining the dark primary that merges visible images in the described step 3) specifically is meant: according to
Figure BDA0000075720090000027
Obtain the dark primary I that merges visible images Dark, wherein c represents r passage, g passage or b passage; I cThe component of the c passage of presentation graphs I, I is the fusion visible images of input, Ω (x) expression is the square area at center with pixel x.
Obtaining the atmosphere light value that merges visible images in the described step 3) specifically is meant: the partly bright spot of extraction from the institute of the dark primary that merges visible images have a few at first, then in the pixel of the bright spot correspondence visible images of described part the value of the pixel of selection intensity maximum as the atmosphere light value.
Obtaining the transmissivity initial value that merges visible images according to dark primary priori in the described step 4) specifically is meant: according to Obtain the transmissivity initial value t ' that merges visible images, wherein c is r passage, g passage or b passage; I cBe the component of c passage of figure I, I is the fusion visible images of input, and Ω is for being the square area at center with pixel x, A cBe the component of the c passage of atmosphere light value, ω is a constant coefficient.
According to soft stingy drawing method the transmissivity initial value is optimized specifically in the described step 4) and is meant: obtain the transmissivity t after the optimization according to t=λ t '/(L+ λ U), wherein L is this matrix of pula, soft stingy Tula, λ is a corrected parameter, and U is the unit matrix with the identical size of L.
Recovering to merge visible images in the described step 5) specifically is meant: according to
Figure BDA0000075720090000031
Obtain final mist elimination image J, wherein I is the fusion visible images of input, and A is the atmosphere light value, and t is the transmissivity after optimizing, t 0Be constant.
The present invention has following advantage: the present invention proposes a kind of image mist elimination algorithm in conjunction with dark primary priori and weighted least-squares wave filter, utilization is based on the single width Misty Image defogging method capable of dark primary priori, and based on the integration technology of the visible images and the near-infrared image of weighted least-squares wave filter, obtain mist elimination image clearly, this algorithm can improve the contrast and the sharpness of Misty Image effectively, increase image detail information, can significantly improve the picture contrast that is caused by fog descends, the situation of deteriroation of image quality such as scenery cross-color and brightness deterioration, obtain high-quality mist elimination image, have the mist elimination clear picture, contrast and sharpness height, the advantage that details is abundant.
Description of drawings
Fig. 1 is the implementing procedure synoptic diagram of the embodiment of the invention;
Fig. 2 is the visible images that the mist scene is arranged of input;
Fig. 3 is the near-infrared image with Fig. 2 Same Scene;
The fused images of Fig. 4 for obtaining by Fig. 2, Fig. 3 according to least squares filtering, promptly preliminary mist elimination image;
Fig. 5 is the dark primary of Fig. 4;
The transmissivity initial value of Fig. 6 for obtaining according to dark primary priori;
Fig. 7 is the optimal value of the transmissivity that obtains according to soft stingy drawing method;
Fig. 8 is for to form the final mist elimination image that model obtains according to mist figure.
Embodiment
As shown in Figure 1, the embodiment of the invention is as follows with the implementation step of the image defogging method capable of image co-registration based on the Misty Image recovery:
1) same visible images and the near-infrared image that the mist scene is arranged of input carries out multi-time weighted least squares filtering respectively with the monochrome information and the near-infrared image of visible images, obtains image luminance information through merging according to the filtering result;
2) with the monochrome information of the alternative former visible images of image luminance information after merging, obtain preliminary mist elimination result;
3) obtain the dark primary that merges visible images, and obtain the atmosphere light value that merges visible images according to dark primary;
4) obtain the transmissivity initial value that merges visible images according to dark primary priori, the transmissivity initial value is optimized the transmissivity after being optimized according to soft stingy drawing method;
5) form model according to mist figure, the transmissivity after utilizing the atmosphere light value and optimizing is recovered to merge visible images, obtains final mist elimination image.
The image luminance information of carrying out multi-time weighted least squares filtering in the step 1) and obtaining through merging according to the filtering result specifically is meant: the monochrome information or the near-infrared image (as shown in Figure 3) of visible images (as shown in Figure 2) are carried out the weighted least-squares filtering first time as input parameter, then current filtering result is carried out multi-time weighted least squares filtering as the input parameter of filtering next time, obtain the input parameter of filtering each time and output result's difference, and with this difference divided by output result when time filtering, obtain contrast images with corresponding many group visible images monochrome informations of filter times and near-infrared image; The contrast images of organizing each group visible images monochrome information and near-infrared image in the contrast images is compared the higher value that obtains wherein more, connect multiplication after then higher value being added 1, to connect the monochrome information that the multiplication result multiply by the visible images of last filtering output again, the image luminance information after obtaining merging.
When being weighted least squares filtering in the step 1), the expression formula of weighted least-squares filtering is
Figure BDA0000075720090000041
Wherein
Figure BDA0000075720090000042
Be the input parameter of the k time filtering, Z represents the monochrome information or the near-infrared image of the preliminary mist elimination image imported,
Figure BDA0000075720090000043
Be the output parameter of the k time filtering and the input parameter of the k+1 time filtering,
Figure BDA0000075720090000044
Be the weighted least-squares wave filter.
In the present embodiment, the weighted least-squares wave filter
Figure BDA0000075720090000045
Expression formula be
Figure BDA0000075720090000046
λ wherein 0c kBe the k time filtering result's roughness, λ 0The roughness of input parameter when carrying out filtering for the first time, c is a constant coefficient, k is the filtering sequence number, L gBe Laplce's matrix, U is and L gThe unit matrix of identical size.In the present embodiment, λ 0=0.1, c=2.
The expression formula of Laplce's matrix is
Figure BDA0000075720090000047
D xAnd D yBe discrete differential operator, A x, A yBe diagonal matrix, its element definition is
Figure BDA0000075720090000048
L represents the constant logarithm value of the monochrome information of input picture, p remarked pixel position, and α is a constant coefficient, in the present embodiment, α=1.2, ε is a very little constant, ε in the present embodiment=0.0001.
Through after six filtering, ask for filtering result's each time contrast images (contrastimage) according to following formula in the present embodiment:
Z k + 1 d = Z k a - Z k + 1 a Z k + 1 a
Wherein k is the wave filter sequence number of passing through, span from 1 to 6; Z a kBe the input parameter of k wave filter, Z represents monochrome information V or near-infrared image N; Z a K+1It is the output parameter of k wave filter; Z d K+1It is the output result's of k wave filter contrast images.Each the group contrast images that obtains is made comparisons and got maximal value, connect after adding 1 and take advantage of, the value that obtains be multiply by the monochrome information of last wave filter output again, the image luminance information after promptly obtaining merging, as shown in the formula:
F 0 = V n + 1 a Π k = 1 n ( max ( V k + 1 d , N k + 1 d ) + 1 )
Wherein n is filter times (n=6 in this experiment); V a N+1It is the visible images monochrome information of n wave filter output; V d K+1It is the contrast images of the visible images monochrome information of k wave filter output; N d K+1It is the contrast images of the near-infrared image of k wave filter output; ∏ takes advantage of symbol for connecting.
Image after the fusion as shown in Figure 4.
Obtaining the dark primary that merges visible images in the step 3) specifically is meant: according to
Figure BDA0000075720090000052
Obtain the dark primary I that merges visible images Dark, wherein c represents r passage, g passage or b passage; I cThe component of the c passage of presentation graphs I, I is the fusion visible images of input, Ω (x) expression is the square area at center with pixel x.Ω (x) area size should be advisable with the lucky white object that can cover except that day dummy section, and in the present embodiment, the pixel size of near-infrared image and visible images is 563*373, and Ω (x) area size is the zone of 9*9 size.Dark primary as shown in Figure 5.
Obtaining the atmosphere light value that merges visible images in the step 3) specifically is meant: at first from the institute of the dark primary that merges visible images have a few, extract partly bright spot, then in the pixel of partly bright spot correspondence visible images the value of the pixel of selection intensity maximum as the atmosphere light value.When present embodiment extracted the bright spot of part, the bright spot of extracting 0.1% quantity was as the bright spot of part.
Obtaining the transmissivity initial value that merges visible images according to dark primary priori in the step 4) specifically is meant: according to
Figure BDA0000075720090000053
Obtain the transmissivity initial value t ' that merges visible images, wherein c is r passage, g passage or b passage; I cBe the component of c passage of figure I, I is the fusion visible images of input, and Ω is for being the square area at center with pixel x, A cBe the component of the c passage of atmosphere light value, ω is a constant coefficient.But ω value 0＜ω≤1, ω in the present embodiment=0.8.Dark primary priori is from the statistical law to the no mist image data base in open air, and it is based on through observable so ultimate facts---and all there is the very low pixel of intensity level of some at least one Color Channel in each regional area of most no mist images in open air.Utilize this priori to analyze the mist elimination model, we can directly estimate the depth information of the transmissivity and the scene of image.According to
Figure BDA0000075720090000054
Calculate transmissivity initial value t ' time of visible images and used dark primary priori, its derivation is as follows:
In computer vision and the computer graphical, the described mist figure of following equation forms model and is widely used:
I(x)＝J(x)t(x)+A(1-t(x))
Wherein, I is meant the intensity of the image that observes, and J is the intensity of scenery light, and A is the global atmosphere light component, and t is used for describing light and is transmitted to the part that is not scattered in the camera process by media, is called transmissivity.
Suppose that the transmissivity at a regional area is invariable, forming equation by mist figure can obtain:
I A = J A t + 1 - t
Following formula the right and left is all carried out and calculating dark primary identical operations, have
min Ω ( min c I c A c ) = { min Ω ( min c J c A c ) } t + 1 - t
According to dark primary priori min Ω(min cJ c) → 0, following formula can be write as
t = 1 - min Ω ( min c I c A c )
In the reality, even bright day gas always comprises some impurity molecules inevitably very much in the air.Therefore, introduce a constant ω (＜ω≤1), keep the mist that a part covers remote scenery targetedly, thereby finally obtain expression formula t ′ = 1 - ω min c ( min Ω I c A c ) .
The initial value of transmissivity as shown in Figure 6.
According to soft stingy drawing method the transmissivity initial value is optimized specifically in the step 4) and is meant: obtain the transmissivity t after the optimization according to t=λ t '/(L+ λ U), wherein L is this matrix of pula, soft stingy Tula, U is and the unit matrix of the identical size of L that λ is a corrected parameter, λ in the present embodiment=10 -6It is identical with stingy figure equation in form that mist figure forms model equation, and it is Alpha's distribution that the distribution of transmissivity can be regarded.Therefore, the transmissivity after the optimization can be tried to achieve by minimizing following cost function:
E(t)＝t TLt+λ(t-t′) T(t-t′)。
Element L in this matrix of pula, soft stingy Tula (i j) is defined as follows:
Σ k | ( i , j ) ∈ ( δ ij - 1 | w k | ( 1 + ( I i - μ k ) T ( Σ k + ϵ | w k | U 3 ) - 1 ( I j - μ k ) ) )
Wherein, w kFor being the window of the 3*3 pixel size at center with pixel k, | w k| be w kThe number of pixels of window area, δ IjBe Kronecker symbol, I iBe the matrix of a 3*1, three elements are respectively r, g, the b information of input picture at i pixel place; I jBe the matrix of a 3*1, three elements are respectively r, g, the b information of input picture at j pixel place; μ kBe window w kThe mean value of element in the window area; ∑ kBe w kThe variance of element in the window area; U 3Be the unit matrix of a 3*3, ε also is a corrected parameter, ε in the present embodiment=10 -3
The initial value of transmissivity as shown in Figure 7.
Recovering to merge visible images in the step 5) specifically is meant: according to
Figure BDA0000075720090000071
Obtain final mist elimination image J, wherein I is the fusion visible images of input, and A is the atmosphere light value, and t is the transmissivity after optimizing, t 0Be constant, t in the present embodiment 0=0.1.Final mist elimination image as shown in Figure 8.
The above only is a preferred implementation of the present invention, and protection scope of the present invention is not limited in above-mentioned embodiment, and every technical scheme that belongs to the principle of the invention all belongs to protection scope of the present invention.For a person skilled in the art, some improvements and modifications of under the prerequisite that does not break away from principle of the present invention, carrying out, these improvements and modifications also should be considered as protection scope of the present invention.

Claims (9)

1. one kind is restored image defogging method capable with image co-registration based on Misty Image, it is characterized in that implementation step is as follows:
1) same visible images and the near-infrared image that the mist scene is arranged of input carries out multi-time weighted least squares filtering respectively with the monochrome information and the near-infrared image of visible images, obtains image luminance information through merging according to the filtering result;
2) with the monochrome information of the alternative former visible images of image luminance information after merging, obtain preliminary mist elimination result;
3) obtain the dark primary that merges visible images, and obtain the atmosphere light value that merges visible images according to dark primary;
4) obtain the transmissivity initial value that merges visible images according to dark primary priori, the transmissivity initial value is optimized the transmissivity after being optimized according to soft stingy drawing method;
5) form model according to mist figure, utilize the transmissivity after described atmosphere light value and the described optimization to recover described fusion visible images, obtain final mist elimination image.
2. according to claim 1 based on the image defogging method capable of Misty Image recovery with image co-registration, the image luminance information that it is characterized in that carrying out multi-time weighted least squares filtering in the described step 1) and obtain through merging according to the filtering result specifically is meant: the monochrome information or the near-infrared image of visible images are carried out the weighted least-squares filtering first time as input parameter, then current filtering result is carried out multi-time weighted least squares filtering as the input parameter of filtering next time, obtain the input parameter of filtering each time and output result's difference, and with this difference divided by output result when time filtering, obtain contrast images with corresponding many group visible images monochrome informations of filter times and near-infrared image; Each the group visible images monochrome information in described many group contrast images and the contrast images of near-infrared image are compared the higher value that obtains wherein, connect multiplication after then higher value being added 1, to connect the monochrome information that the multiplication result multiply by the visible images of last filtering output again, the image luminance information after obtaining merging.
3. according to claim 2 based on the image defogging method capable of Misty Image recovery with image co-registration, it is characterized in that: when being weighted least squares filtering in the described step 1), the expression formula of weighted least-squares filtering is
Figure FDA0000075720080000011
Wherein
Figure FDA0000075720080000012
Be the input parameter of the k time filtering, Z represents the monochrome information or the near-infrared image of the preliminary mist elimination image imported,
Figure FDA0000075720080000013
Be the output parameter of the k time filtering and the input parameter of the k+1 time filtering,
Figure FDA0000075720080000014
Be the weighted least-squares wave filter.
4. according to claim 3 based on the image defogging method capable of Misty Image recovery with image co-registration, it is characterized in that: described weighted least-squares wave filter
Figure FDA0000075720080000015
Expression formula be
Figure FDA0000075720080000016
λ wherein 0c kBe the k time filtering result's roughness, λ 0The roughness of input parameter when carrying out filtering for the first time, c is a constant coefficient, k is the filtering sequence number, L gBe Laplce's matrix, U is and L gThe unit matrix of identical size.
5. according to claim 1 based on the image defogging method capable of Misty Image recovery with image co-registration, it is characterized in that obtaining in the described step 3) dark primary that merges visible images and specifically be meant: according to
Figure FDA0000075720080000017
Obtain the dark primary I that merges visible images Dark, wherein c represents r passage, g passage or b passage; I cThe component of the c passage of presentation graphs I, I is the fusion visible images of input, Ω (x) expression is the square area at center with pixel x.
6. according to claim 5 based on the image defogging method capable of Misty Image recovery with image co-registration, it is characterized in that obtaining in the described step 3) atmosphere light value that merges visible images specifically is meant: the partly bright spot of extraction from the institute of the dark primary that merges visible images have a few at first, then in the pixel of the bright spot correspondence visible images of described part the value of the pixel of selection intensity maximum as the atmosphere light value.
7. according to claim 1 based on the image defogging method capable of Misty Image recovery with image co-registration, it is characterized in that obtaining the transmissivity initial value that merges visible images according to dark primary priori in the described step 4) specifically is meant: according to
Figure FDA0000075720080000021
Obtain the transmissivity initial value t ' that merges visible images, wherein c is r passage, g passage or b passage; I cBe the component of c passage of figure I, I is the fusion visible images of input, and Ω is for being the square area at center with pixel x, A cBe the component of the c passage of atmosphere light value, ω is a constant coefficient.
8. according to claim 7 based on the image defogging method capable of Misty Image recovery with image co-registration, it is characterized in that in the described step 4) transmissivity initial value being optimized specifically and be meant: obtain the transmissivity t after the optimization according to t=λ t '/(L+ λ U) according to soft stingy drawing method, wherein L is this matrix of pula, soft stingy Tula, λ is a corrected parameter, and U is the unit matrix with the identical size of L.
9. according to any described image defogging method capable in the claim 1～8, it is characterized in that recovering to merge visible images in the described step 5) specifically is meant based on Misty Image recovery and image co-registration: according to Obtain final mist elimination image J, wherein I is the fusion visible images of input, and A is the atmosphere light value, and t is the transmissivity after optimizing, t 0Be constant.
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