CN106960421A - Evening images defogging method based on statistical property and illumination estimate - Google Patents
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
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- G06T5/00—Image enhancement or restoration
- G06T5/40—Image enhancement or restoration using histogram techniques
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/90—Dynamic range modification of images or parts thereof
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
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- G06T2207/10024—Color image
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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Abstract
The invention discloses a kind of evening images defogging method based on statistical property and illumination estimate, including:Night foggy image is inverted into obtain reverse image;The local atmosphere light with colour cast of reverse image is calculated, and is optimized by directiveness filtering;The initial transmission of triple channel and the rough estimate transmissivity of triple channel are calculated, the rough estimate transmissivity of triple channel is corrected using the bright passage of reverse image, and obtains optimizing transmissivity by directiveness filtering:To solve carry out again after restored image using atmosphere light of the part with colour cast and optimization transmissivity and invert and obtain mist elimination image of the night with colour cast;And color correction is carried out using local grey word, finally give night mist elimination image.The evening images mist elimination image obtained using the present invention can not only effectively recover brightness, the contrast of image, moreover it is possible to effectively correct the colour cast of evening images, significantly improve visual effect, while retaining more image detail informations, and substantially reduce computational complexity.
Description
Technical field
The present invention relates to a kind of Computer Image Processing method, more particularly to a kind of evening images defogging method.
Background technology
When there is shooting image under mist environment at night, image overall gray value and contrast can be caused to reduce and lose a large amount of
Detailed information, it is difficult to recognize region interested, brought to video monitoring, outdoor target identification and tracking, remotely sensed image etc.
Very big difficulty.Therefore, evening images defogging problem is urgently to be resolved hurrily in computer vision application field and digital image processing field.
Existing evening images defogging method is less, mainly there is Pei[1]What is proposed is changed based on dark primary priori and color
Evening images defogging algorithm, Zhang[2]The defogging algorithm and Li based on new model proposed[3]Based on relative smooth about
Hierachical decomposition defogging algorithm of beam etc..The defogging main frame of these algorithms is still based on dark primary priori, but is due to night
The special imaging circumstances of foggy image, dark primary priori is under night environment and does not apply to, therefore these algorithms restore the figure
Picture is overall partially dark, and the cross-color of various degrees, and substantially, defogging is incomplete for Halo effect at image light source,
And calculate complicated.
[bibliography]
[1]Pei S C,Lee T Y.Nighttime haze removal using color transfer pre-
processing and dark channel prior[A].Proceedings of the IEEE International
Conference on Image Processing[C].Orlando:IEEE Computer Society Press,2012,
957-960。
[2]Zhang J,Cao Y,Wang Z.Nighttime haze removal based on a new imaging
model[A].Proceedings of the IEEE International Conference on Image Processing
[C].Paris:IEEE Computer Society Press,2014.4557-4561。
[3]Li Y,Tan R T,Brown S Michael.Nighttime haze remov-al with glow and
multiple light colors[C].Proceedings of IEEE International Conference on
Computer Vi-sion.Santiago:IEEE Computer Society Press,2015:226-234。
[4]He K,Sun J,Tang X.Single image haze removal using dark channel
prior[J].Pattern Analysis and Machine Intelligence,IEEE Transactions on,2011,
33(12):2341-2353。
[5]G.Buchsbaum.A spatial processor model for object colour
perception.Journal of the Franklin Institute,1980,310(80):1–26。
[6]Meng Gaofeng,WANG Ying,DUAN Jiangyong,et al.Efficient image
dehazing with boundary constraint and contextual regularization[C].IEEE
International Con-ference on Computer Vision(ICCV),Sydney,Australia,2013:617-
624。
[7]X.Dong,J.T.Wen,W.X.Li,An efficient and integrated algorithm for
video enhancement in challenging lighting conditions,in Proceedings of
Institute of Electrical and Electronic Engineers International Conference on
Computer Vision and Pattern Recognition,pp.1241-1249,2011。
The content of the invention
Regarding to the issue above, the present invention proposes a kind of evening images defogging method based on statistical property and illumination estimate.
First the night foggy image new model with the colour cast factor is set up according to the special imaging circumstances of night foggy image;Then lead to
The bright channel histogram distribution of the reverse image of statistics night foggy image and low-light (level) image is crossed, by night foggy image defogging
Problem is converted into low-light (level) image enhaucament problem, and utilizes improved He[4]The local atmosphere light with colour cast of method estimation, simultaneously
Transmissivity is corrected by the bright passage of the reverse image of night foggy image thin to retain the more edges of mist elimination image
Information is saved, finally by local grey-world[5]Color correction is carried out to mist elimination image.Evening images defogging side of the present invention
Method can not only effectively recover brightness, the contrast of image, moreover it is possible to effectively correct the colour cast of evening images, significantly improve vision effect
Really, while retaining more image detail informations, and computational complexity is substantially reduced.
In order to solve the above-mentioned technical problem, a kind of evening images based on statistical property and illumination estimate proposed by the present invention
Defogging method, step is as follows:
Step 1, the night foggy image of input are image I (x), and image I (x) is inverted to obtain into reverse image
In formula (1), c ∈ { r, g, b };
Step 2, calculating reverse imageThe local atmosphere light r with colour castL(x)AL(x), and by directiveness filter into
Row optimization:
In formula (2), Ω (x) is pixel x local neighborhood, and Ω (y) is neighborhood y local neighborhood, and GF represents guiding filter
Ripple;
Step 3, calculating reverse imageTriple channel initial transmission taL(x) with the rough estimate transmissivity of triple channel
tbL(x):
Step 4, utilize reverse imageBright passage to the rough estimate transmissivity t of triple channelbL(x) it is corrected, and leads to
Directiveness filtering is crossed to optimize:
tL(x)=GF (eA_lighttbL(x)) (6)
In formula (5) and formula (6):A_light is reverse imageBright passage, tL(x) it is saturating for the rough estimate to triple channel
Penetrate rate tbL(x) the optimization transmissivity after correcting;
Step 5, the local atmosphere light r with colour cast solved using above-mentioned steps 2L(x)AL(x) optimization obtained with step 4
Transmissivity tL(x) restored image r is solvedL(x)JL(x):
In formula (7):ε is fixed constant, ε=0.1;
Step 6, to restored image rL(x)JL(x) progress inverts and obtains mist elimination image J of the night with colour cast againp(x):
Jp(x)=255-r (x) J (x) (8)
Step 7, using local grey word to mist elimination image J of the night with colour castp(x) color correction is carried out, is obtained
Final night mist elimination image J (x),
In formula (9):ω represents whole visible-range, and λ is optical wavelength, and e (λ) represents the distribution of the light of certain wave band, s (x,
Be λ) that certain point is to the reflectivity of a certain wavelength in space, p (λ) represents photobehavior of the camera to certain light, m be [0,1] it
Between a constant.
Compared with prior art, the beneficial effects of the invention are as follows:
The present invention carries out defogging based on statistical property to evening images, and night foggy image can be regarded as to low-light (level) image
Handled, ask for the local atmosphere light with colour cast using the He improved the method for asking for atmosphere light, and utilize reversion figure
The bright passage of picture is corrected to rough estimate transmissivity further to retain the details and monochrome information of image, finally by part
Grey world carry out color correction to restored image has the robustness of mist scene to multiple light courcess night to improve algorithm.
Brief description of the drawings
Fig. 1 (a) is the bright channel histogram of the reverse image of night foggy image;
Fig. 1 (b) is the bright channel histogram of the reverse image of low-light (level) image;
Fig. 2 (a) is a width night foggy image Trains;
Fig. 2 (b) is defogging algorithm of the document [2] based on new model to the result after image Trains processing;
Fig. 2 (c) is after document [3] is handled image Trains based on the hierachical decomposition defogging algorithm that relative smooth is constrained
As a result;
Fig. 2 (d) is the result that evening images defogging method of the present invention is handled image Trains;
Fig. 3 (a) is a width night foggy image Street;
Fig. 3 (b) is defogging algorithm of the document [2] based on new model to the result after image Street processing;
Fig. 3 (c) is after document [3] is handled image Street based on the hierachical decomposition defogging algorithm that relative smooth is constrained
As a result;
Fig. 3 (d) is the result that evening images defogging method of the present invention is handled image Street.
Embodiment
Technical solution of the present invention is described in further detail with specific embodiment below in conjunction with the accompanying drawings, described is specific
Only the present invention is explained for embodiment, is not intended to limit the invention.
The mentality of designing of evening images defogging method of the present invention is as follows:
1st, the algorithm general principle in common evening images defogging method is:According to document [2], night foggy image into
As model:
I (x)=r (x) (J (x) t (x)+(1-t (x)) A (x)) is 1.
Wherein, I (x) is night foggy image, and J (x) is night mist elimination image, and t (x) is transmissivity, and A (x) is bias light
Intensity, r (x) is the colour cast factor.
According to boundary constraint[6], the initial transmission t of Misty Image can be obtaineda(x) with rough estimate transmissivity tb(x):
And then obtain night picture rich in detail:
For low-light (level) image IL(x), first it is inverted:
RL(x)=255-IL(x) ⑤
Afterwards by RL(x) 4. substitution formula obtains:
To JL(x) inverted again, obtain last enhancing image.
2nd, led to by contrasting the bright of reverse image of the 50 width night foggy images randomly selected and 50 width low-light (level) images
The histogram distribution in road, such as Fig. 1 (a) and Fig. 1 (b) are shown.It was found that the reverse image tool of night foggy image and low-light (level) image
There is great similitude, therefore night foggy image defogging problem can be converted into low-light (level) image enhaucament problem, according to document
[7], the reverse image of low-light (level) image is considered as foggy image on daytime, similar, the reverse image of night foggy image
Foggy image on daytime can approximately be regarded as to be handled, but be due to the presence of night environment colour cast, the reversion of night foggy image
Image is still even with uneven illumination, the attribute such as colour cast, and existing defogging algorithm is not still applied to, evening images defogging of the present invention
Atmosphere light and colour cast are handled as an entirety in method and utilize improved He methods to estimate the atmosphere light with colour cast,
It is serious for night foggy image colour cast, cause triple channel transmission difference larger, it is right in evening images defogging method of the present invention
The initial transmission that 2. above-mentioned formula calculates carries out three-channel processing simultaneously in order to retain more image details, passes through reverse image
Bright passage rough estimate transmissivity is corrected and optimized using directiveness filtering, finally by local grey world
Color correction is carried out to mist elimination image.
Evening images defogging method proposed by the present invention based on statistical property and illumination estimate, is comprised the following steps that:
Step 1, the night foggy image of input are image I (x), and image I (x) is inverted to obtain into reverse image
In formula (1), c ∈ { r, g, b }, x is the position of pixel in image I (x);
Step 2, calculating reverse imageThe local atmosphere light r with colour castL(x)AL(x), and by directiveness filter into
Row optimization:
In formula (2), Ω (x) is pixel x local neighborhood, and Ω (y) is field y local neighborhood, and GF represents guiding filter
Ripple;
Step 3, in order that transmissivity solves more accurate, the method that document [6] calculates transmissivity is improved, calculated
The initial transmission t of triple channelaL(x) with the rough estimate transmissivity t of triple channelbL(x):
Step 4, in order that transmissivity local smoothing method and keeping good light characteristic, utilize reverse imageIt is bright
Rough estimate transmissivity t of the passage to triple channelbL(x) it is corrected, and is optimized by directiveness filtering:
tL(x)=GF (eA_lighttbL(x)) (6)
In formula (5) and formula (6):A_light is reverse imageBright passage, tL(x) it is saturating for the rough estimate to triple channel
Penetrate rate tbL(x) the optimization transmissivity after correcting;
Step 5, the local atmosphere light r with colour cast solved using above-mentioned steps 2L(x)AL(x) optimization obtained with step 4
Transmissivity tL(x) restored image r is solvedL(x)JL(x):
In formula (7):ε is fixed constant, and it is that zero, ε takes 0.1 to prevent denominator.
Step 6, to restored image rL(x)JL(x) progress inverts and obtains mist elimination image J of the night with colour cast againp(x):
Jp(x)=255-r (x) J (x) (8)
Step 7, in order to improve robustness of the algorithm to night multiple light courcess scene, using the grey proposed in document [5]
Word algorithms simultaneously carry out localization improvement to mist elimination image J of the night with colour castp(x) color correction is carried out, night is finally given
Mist elimination image J (x),
In formula (9):ω represents whole visible-range, and λ is optical wavelength, and e (λ) represents the distribution of the light of certain wave band, s (x,
Be λ) that certain point is to the reflectivity of a certain wavelength in space, p (λ) represents photobehavior of the camera to certain light, m be [0,1] it
Between a constant.
In order to verify the validity of evening images defogging method proposed by the present invention, defogging is carried out to night foggy image real
Test, and contrasted with related algorithm.Fig. 2 (a) is that width night foggy image a Trains, Fig. 2 (b) is to be carried using document [2]
The defogging algorithm based on new model gone out is to the defog effect after image Trains processing, and Fig. 2 (c) is to be proposed using document [3]
Based on relative smooth constrain hierachical decomposition defogging algorithm to image Trains processing after defog effect, Fig. 2 (d) be this hair
Bright evening images defogging method image Trains is handled after defog effect.Fig. 3 (a) is a width night foggy image
Street, Fig. 3 (b) are the defogging algorithm based on new model proposed using document [2] to the defogging after image Street processing
As a result, Fig. 3 (c) is the hierachical decomposition defogging algorithm based on relative smooth constraint proposed using document [3] to image Street
Defogging result after processing;Fig. 3 (d) is the defogging knot after evening images defogging method of the present invention is handled image Street
Really.As can be seen that the night mist elimination image obtained after being handled using evening images defogging method of the present invention and document [2] Zhang
The hierachical decomposition defogging algorithm constrained based on relative smooth that the defogging algorithm based on new model and document [3] Li proposed is proposed
Compared to brightness of image and contrast balanced can be improved, the halo artifact that source region is brought effectively is removed, and can recover more
Image detail information, the colour cast of correction chart picture is visual with more preferable visual effect.
For objective evaluation evening images defogging method of the present invention, the colour cast degree and contrast of night mist elimination image are calculated.
As shown in table 1.
The objective indicator comparative result of table 1
Shown by the colour cast level data of table 1, the inventive method can effective correction chart picture colour cast;It can be seen by contrast results
Go out, the inventive method can improve the overall contrast of the image after defogging.
Test result indicate that, the evening images defogging method proposed by the present invention based on statistical property and illumination estimate can pin
The colour cast of the defect that evening images defogging has, effectively correction evening images is carried out based on dark primary method to tradition, is retained
More image details, equilibrium improves the overall brightness and contrast of image, with more preferable sense of vision.
Although above in conjunction with accompanying drawing, invention has been described, and the invention is not limited in above-mentioned specific implementation
Mode, above-mentioned embodiment is only schematical, rather than restricted, and one of ordinary skill in the art is at this
Under the enlightenment of invention, without deviating from the spirit of the invention, many variations can also be made, these belong to the present invention's
Within protection.
Claims (1)
1. a kind of evening images defogging method based on statistical property and illumination estimate, it is characterised in that step is as follows:
Step 1, the night foggy image of input are image I (x), and image I (x) is inverted to obtain into reverse image
In formula (1), c ∈ { r, g, b };
Step 2, calculating reverse imageThe local atmosphere light r with colour castL(x)AL(x), and by directiveness filtering carry out excellent
Change:
In formula (2), Ω (x) is pixel x local neighborhood, and Ω (y) is neighborhood y local neighborhood, and GF represents guiding filtering;
Step 3, calculating reverse imageTriple channel initial transmission taL(x) with the rough estimate transmissivity t of triple channelbL
(x):
Step 4, utilize reverse imageBright passage to the rough estimate transmissivity t of triple channelbL(x) it is corrected, and by referring to
The property led filtering is optimized:
tL(x)=GF (eA_lighttbL(x)) (6)
In formula (5) and formula (6):A_light is reverse imageBright passage, tL(x) it is the rough estimate transmissivity to triple channel
tbL(x) the optimization transmissivity after correcting;
Step 5, the local atmosphere light r with colour cast solved using above-mentioned steps 2L(x)AL(x) the optimization transmission obtained with step 4
Rate tL(x) restored image r is solvedL(x)JL(x):
In formula (7):ε is fixed constant, ε=0.1;
Step 6, to restored image rL(x)JL(x) progress inverts and obtains mist elimination image J of the night with colour cast againp(x):
Jp(x)=255-r (x) J (x) (8)
Step 7, using local grey word to mist elimination image J of the night with colour castp(x) color correction is carried out, obtains final
Night mist elimination image J (x),
In formula (9):ω represents whole visible-range, and λ is optical wavelength, and e (λ) represents the distribution of the light of certain wave band, and s (x, λ) is
Certain point is to the reflectivity of a certain wavelength in space, and p (λ) expression cameras are to the photobehavior of certain light, and m is between [0,1]
One constant.
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CN113112429A (en) * | 2021-04-27 | 2021-07-13 | 大连海事大学 | Universal enhancement framework for foggy images under complex illumination condition |
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