CN106997584A - A kind of haze weather image enchancing method - Google Patents
A kind of haze weather image enchancing method Download PDFInfo
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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
- G06T5/73—Deblurring; Sharpening
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
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Abstract
Former haze weather coloured image is changed to HSV space from rgb space；Processing is filtered to lightness V, tone H, saturation degree S and lightness V synthesize to obtain image 1；Described image 1 is changed to the rgb space from the HSV space again, the rgb space image 2 is obtained；Described image 2 is handled with multi-Scale Retinex Algorithm, haze weather coloured image is divided into incident components L and reflecting component R；Gamma transformation is carried out to the incident components L, bilateral filtering is carried out to the reflecting component R, image 3 is obtained；Enhancing processing is carried out with Sigmoid functions to described image 3, final image 4 is obtained.
Description
Technical field
The present invention relates to image enhancement technique field, more particularly to a kind of haze weather image enchancing method.
Background technology
Serious due to environmental pollution in recent years, haze weather takes place frequently, in haze weather, due to the effect of atmospheric scattering,
Cross-color, the contrast of captured image also decrease, and the total quality of image can also decline so that intelligent camera system
The picture quality that system is extracted produces degeneration, and the visual effect of image is influenceed by serious, thus needs to the figure before output
As carrying out enhancing processing, the vision system for making it be more suitable for the mankind.
Existing image enchancing method is mostly carried out in rgb space, and in rgb space, if distinguishing R, G, B component
Different degrees of adjustment is carried out, the ratio shared by each component will be changed, changes the colour information of image.
And current existing Misty Image Enhancement Method, such as Homomorphic Filtering Algorithm and multi-Scale Retinex Algorithm are all
Rudimentary algorithm in image enhaucament, with very strong application, but the problem of be also individually present certain, homomorphic filtering first is calculated
Method, the filtering in application due to image on frequency domain is, towards entire image, just inevitably to remove some useful
Information；Although secondly multi-Scale Retinex Algorithm can preferably keep the color of image, also there is certain limitation, hold
It is also easy to produce halation.
Therefore for the image of haze sky, a kind of suitable enhancing algorithm is found in urgent requirement, is more suitable for it
The visual characteristic of human eye and the identification requirement of machine.
The content of the invention
In order to overcome the above-mentioned deficiencies of the prior art, the invention provides a kind of haze weather image enchancing method, to increase
The contrast of strong Misty Image, recovers the color of Misty Image, makes it more natural, clear.
In order to reach above-mentioned purpose, the technical solution adopted in the present invention is a kind of haze weather image enhaucament side
Method, including：
A kind of haze weather image enchancing method, former haze weather coloured image is changed to HSV space from rgb space；To bright
Degree V is filtered processing, and tone H, saturation degree S and lightness V synthesize to obtain image 1；By described image 1 again from described
HSV space is changed to the rgb space, obtains the rgb space image 2；Described image 2 is used into multi-Scale Retinex Algorithm
Handled, haze weather coloured image is divided into incident components L and reflecting component R；Gamma change is carried out to the incident components L
Change, bilateral filtering is carried out to the reflecting component R, image 3 is obtained；Described image 3 is carried out at enhancing with Sigmoid functions
Reason, obtains final image 4.
Color parameter red, green, the blueness in the rgb space model are changed to described by following formula
Color parameter tone H, saturation degree S, lightness V in HSV space model：
R, G, B span are in formula, and the span of the HSV space is respectively,The maximum in the RGB component is represented,
Represent the minimum value in the RGB component.
In the HSV space, keep the tone H, saturation degree S constant, using following formula, the lightness V is carried out
Homomorphic filtering is handled：
WhereinWithThe increased multiple of radio-frequency component and the multiple of low-frequency component reduction are expressed as, is metAnd；For sharpening coefficient and,For cut-off frequency radius,ForArrive filter center
Distance.
To with the tone H, saturation degree S synthesize obtaining image 1 after the filtered lightness V processing, the figure
Changed again from the HSV space to the rgb space as 1.
Sharpening processing is carried out to the image 2 for obtaining the rgb space using the multi-Scale Retinex Algorithm, by institute
State image 2 and be decomposed into the incident components L and the reflecting component R；Using following formula, gamma is used to the incident components L
Conversion carries out illuminance correction：
WhereinFor incident components,For the component after gamma transformation is handled,WithFor constant.
Using following formula, bilateral filtering is carried out to the reflecting component R：
In formula,For image after bilateral filtering,For normaliztion constant,For the image before processing,For brightness similarity,ForPoint is arrivedThe Euclidean distance of point.
The incident components L after the processing and reflecting component R is synthesized, image 3 is obtained, uses following formula, it is right
Described image 3 carries out enhancing processing with Sigmoid functions, obtains final image 4.
WhereinIt is the gradation of image function after image progress contrast stretching,It is at different levels in image
Primitive definition,It is Sigmoid mapping function.Compared with prior art, the beneficial effects of the invention are as follows：
Haze weather image is changed to HSV color spaces from rgb color space, the color information of image is maintained well；
And homomorphic filtering processing is carried out, the illumination of image can be corrected；To the gamma correction of incident components, image can be carried out
Non-linear tone editor, improves the contrast of image；To the bilateral filtering of reflecting component, can not only remove image noise but also can
To keep the marginal information of image；Sigmoid functions reach the purpose for further enhancing image.The haze weather image of the present invention
Enhancement Method removes haze effect significantly, and the image after processing becomes apparent from, and color is more naturally, more have visuality.
Brief description of the drawings
Fig. 1 is a kind of schematic flow sheet of haze weather image enchancing method of the present invention.
Embodiment
The present invention is further described below in conjunction with the accompanying drawings：
It is as shown in Figure 1 a kind of schematic flow sheet of haze weather image enchancing method of the invention, a kind of haze weather image
Enhancement Method comprises the following steps：
Step A1, former haze weather coloured image is changed to HSV space from rgb space；Step A2, keeps tone and saturation degree
It is constant, processing is only filtered to lightness, the image after being handled；Step A3, then changes image from HSV space again
To rgb space, rgb space coloured image is obtained；Step A4, obtained image is handled with Retinex algorithm, by its point
For incident components and reflecting component；Gamma transformation is carried out to incident components, bilateral filtering is carried out to reflecting component, obtained after output
Image；Step A5, enhancing processing is carried out to the image after output with Sigmoid functions,
A kind of idiographic flow of each several part of haze weather image enchancing method of the detailed description below present invention：
In step A1, a kind of haze weather image enchancing method of the invention is by original haze weather coloured image rgb space
The color parameter tone that color parameter is red, green, blueness conversion are into HSV space model in model, saturation degree, lightness,
RGB pattern is also three primary colors pattern, in RGB patterns, and R represents red light, and G represents green light, and B represents blue light,
The brightness value of these three colors is allocated, new colored pixels can be produced,
HSV patterns are the color spaces created according to the intuitive of color, and H represents tone in this space, and S represents full
And degree, V represents lightness,
Due to can preferably keep the color information of image, a kind of haze of the present invention to image progress processing in HSV space
In weather image Enhancement Method, by rgb space model conversion to HSV space model, conversion formula is as follows：
R, G, B span are in formula, and HSV span is respectively,The maximum in RGB component is represented,Represent
Minimum value in RGB component, goes to step A2
In step A2, the tone H of the image of HSV space, saturation degree S are kept constant, lightness V is carried out at homomorphic filtering
Reason, using transmission function of the bi-exponential function as homomorphic filtering, is handled image with below equation：
WhereinTo enter the image after homomorphic filtering processing,Pass through for original image after Fourier transform
Value,For transmission function,WithIt is expressed as times that the increased multiple of radio-frequency component and low-frequency component are reduced
Number, meetsAnd；For sharpening coefficient and,For cut-off frequency radius,ForTo the distance of filter center, the image irradiation entered after homomorphic filtering processing is corrected, and goes to step A3
In step A3, the image below equation of HSV space after treatment is changed into RGB color space：
In step A4, the coloured image of the rgb space using multi-Scale Retinex Algorithm to obtaining carries out sharpening processing,
Obtained coloured image is decomposed into incident components L and reflecting component R；Using following formula, to incident components gamma transformation
Carry out illuminance correction：
WhereinFor incident components,For the component after gamma transformation is handled,WithFor constant, gamma school
Can just non-linear tone editor be carried out to image, improve the contrast of image,
Using following formula, bilateral filtering is carried out to reflecting component R：
In formula,For image after bilateral filtering,For normaliztion constant,For the image before processing,For brightness similarity,ForPoint is arrivedThe Euclidean distance of point, to the bilateral filtering of reflecting component, both may be used
The marginal information of image can be kept with the noise for removing image again, step A5 is gone to
In step A5, following formula are used, enhancing processing is carried out with Sigmoid functions to the image after output, finally located
Image after reason：
WhereinIt is the gradation of image function after image progress contrast stretching,It is the pixels at different levels in image
Function,It is Sigmoid mapping function.Scenery is more clear in the image after the processing of Sigmoid functions, image,
A kind of overall process of the haze weather image enchancing method described above for being the present invention, but above-mentioned implementation process not uses
To limit the present invention, those skilled in the art under the premise of not departing from the present invention, can make and be correspondingly improved, this hair
Bright protection domain is defined by the scope that claim is defined.
Claims (8)
1. a kind of haze weather image enchancing method, it is characterised in that including：
Former haze weather coloured image is changed to HSV space from rgb space；Processing is filtered to lightness V, by tone H, satisfied
With degree S and lightness V synthesize obtaining image 1；Described image 1 is changed to the rgb space from the HSV space again, obtained
To the rgb space image 2；Described image 2 is handled with multi-Scale Retinex Algorithm, by haze weather coloured image
It is divided into incident components L and reflecting component R；Gamma transformation is carried out to the incident components L, the reflecting component R carried out bilateral
Filtering, obtains image 3；Enhancing processing is carried out with Sigmoid functions to described image 3, final image 4 is obtained.
2. a kind of haze weather image enchancing method according to claim 1, it is characterised in that：By following formula by institute
State the color parameter tone that color parameter is red, green, blueness conversion are into the HSV space model in rgb space model
H, saturation degree S, lightness V：
R, G, B span are in formula, and the span of the HSV space is respectively,The maximum in the RGB component is represented,
Represent the minimum value in the RGB component.
3. a kind of haze weather image enchancing method according to claim 1, it is characterised in that：In the HSV space, keep
The tone H, saturation degree S are constant, and using following formula, homomorphic filtering processing is carried out to the lightness V：
WhereinWithThe increased multiple of radio-frequency component and the multiple of low-frequency component reduction are expressed as, is metAnd；For sharpening coefficient and,For cut-off frequency radius,ForArrive filter center
Distance.
4. a kind of haze weather image enchancing method according to claim 1, it is characterised in that：To the filtered lightness
Synthesized after V processing with the tone H, saturation degree S progress and obtain image 1, described image 1 is changed to institute from the HSV space again
State rgb space.
5. a kind of haze weather image enchancing method according to claim 1, it is characterised in that：Using described multiple dimensioned
Retinex algorithm carries out sharpening processing to the image 2 for obtaining the rgb space, and described image 2 is decomposed into described incident point
Measure the L and reflecting component R；Using following formula, illuminance correction is carried out with gamma transformation to the incident components L：
WhereinFor incident components,For the component after gamma transformation is handled,WithFor constant.
6. a kind of haze weather image enchancing method according to claim 5, it is characterised in that：Using following formula, to institute
State reflecting component R and carry out bilateral filtering：
In formula,For image after bilateral filtering,For normaliztion constant,For the image before processing,For brightness similarity,ForPoint is arrivedThe Euclidean distance of point.
7. a kind of haze weather image enchancing method according to claim 1, it is characterised in that：It will enter described in after processing
Component L and reflecting component R synthesis is penetrated, image 3 is obtained, uses following formula, described image 3 is carried out with Sigmoid functions
Enhancing is handled, and obtains final image 4.
8. whereinIt is the gradation of image function after image progress contrast stretching,It is the pictures at different levels in image
Prime function,It is Sigmoid mapping function.
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| CN107730470A (en) * | 2017-10-18 | 2018-02-23 | 四川理工学院 | A kind of multiple dimensioned improvement Retinex image enchancing methods blocked with histogram of explicit expression |
| CN108288258A (en) * | 2018-04-23 | 2018-07-17 | 电子科技大学 | A kind of low-quality images Enhancement Method under severe weather conditions |
| CN109472758A (en) * | 2018-11-20 | 2019-03-15 | 山东科技大学 | A kind of seismic section image grain details Enhancement Method |
| CN109472755A (en) * | 2018-11-06 | 2019-03-15 | 武汉高德智感科技有限公司 | A kind of domain infrared image logarithm LOG Enhancement Method |
| CN109816608A (en) * | 2019-01-22 | 2019-05-28 | 北京理工大学 | A kind of low-light (level) image adaptive brightness enhancement based on noise suppressed |
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| WO2020107321A1 (en) * | 2018-11-29 | 2020-06-04 | 唐山曹妃甸联城科技有限公司 | Low-light-level image enhancement method and apparatus based on retinex |
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| CN112837249A (en) * | 2020-12-31 | 2021-05-25 | 泉州装备制造研究所 | Low-contrast image enhancement method for welding robot |
| CN114298916A (en) * | 2021-11-11 | 2022-04-08 | 电子科技大学 | X-Ray image enhancement method based on gray stretching and local enhancement |
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| CN107393504A (en) * | 2017-09-11 | 2017-11-24 | 青岛海信电器股份有限公司 | Picture adjustment methods and device based on RGBW panels |
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| CN107730470A (en) * | 2017-10-18 | 2018-02-23 | 四川理工学院 | A kind of multiple dimensioned improvement Retinex image enchancing methods blocked with histogram of explicit expression |
| CN109919846A (en) * | 2017-12-12 | 2019-06-21 | 腾讯科技（深圳）有限公司 | A kind of image enchancing method, device and calculate equipment |
| CN109919846B (en) * | 2017-12-12 | 2022-09-23 | 腾讯科技（深圳）有限公司 | Image enhancement method and device and computing equipment |
| CN108288258B (en) * | 2018-04-23 | 2021-08-10 | 电子科技大学 | Low-quality image enhancement method under severe weather condition |
| CN108288258A (en) * | 2018-04-23 | 2018-07-17 | 电子科技大学 | A kind of low-quality images Enhancement Method under severe weather conditions |
| CN110211049A (en) * | 2018-06-28 | 2019-09-06 | 京东方科技集团股份有限公司 | Image enchancing method, device and equipment based on Retinex theory |
| CN109472755A (en) * | 2018-11-06 | 2019-03-15 | 武汉高德智感科技有限公司 | A kind of domain infrared image logarithm LOG Enhancement Method |
| CN109472758A (en) * | 2018-11-20 | 2019-03-15 | 山东科技大学 | A kind of seismic section image grain details Enhancement Method |
| WO2020107321A1 (en) * | 2018-11-29 | 2020-06-04 | 唐山曹妃甸联城科技有限公司 | Low-light-level image enhancement method and apparatus based on retinex |
| CN109816608A (en) * | 2019-01-22 | 2019-05-28 | 北京理工大学 | A kind of low-light (level) image adaptive brightness enhancement based on noise suppressed |
| CN109816608B (en) * | 2019-01-22 | 2020-09-18 | 北京理工大学 | Low-illumination image self-adaptive brightness enhancement method based on noise suppression |
| CN110276729A (en) * | 2019-06-10 | 2019-09-24 | 浙江工业大学 | A kind of Enhancement Method of low-luminance color image |
| CN110276729B (en) * | 2019-06-10 | 2021-12-17 | 浙江工业大学 | Low-illumination color image enhancement method |
| CN111968065A (en) * | 2020-10-23 | 2020-11-20 | 浙江科技学院 | Self-adaptive enhancement method for image with uneven brightness |
| CN112837249A (en) * | 2020-12-31 | 2021-05-25 | 泉州装备制造研究所 | Low-contrast image enhancement method for welding robot |
| CN114298916A (en) * | 2021-11-11 | 2022-04-08 | 电子科技大学 | X-Ray image enhancement method based on gray stretching and local enhancement |
| CN114298916B (en) * | 2021-11-11 | 2023-04-18 | 电子科技大学 | X-Ray image enhancement method based on gray stretching and local enhancement |
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Application publication date: 20170801 |