CN102629368B - Color image vignetting recovery method based on illumination surface modeling - Google Patents

Color image vignetting recovery method based on illumination surface modeling Download PDF

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CN102629368B
CN102629368B CN201210045873.5A CN201210045873A CN102629368B CN 102629368 B CN102629368 B CN 102629368B CN 201210045873 A CN201210045873 A CN 201210045873A CN 102629368 B CN102629368 B CN 102629368B
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何凯
孔祥文
张伟伟
王伟
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Tianjin Bohua Xinchuang Technology Co.,Ltd.
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Abstract

The invention belongs to the computer image processing field and relates to a color image vignetting recovery method based on illumination surface modeling. The method comprises the following steps: converting an original color vignetting image into an HSI space; extracting foreground and background regions of the vignetting image; using a color image decomposition technology to realize the decomposition of a structure and a texture of the original color vignetting image and acquire a color structure image, and converting the color structure image into the HSI space; in the background region of the image, selecting central points according to an uniformity principle; calculating a radial distance between any two central points; modeling all the points to be modeled and acquiring a curved surface after the modeling; taking the curved surface acquired through modeling as a vignetting function so as to acquire the color image after the vignetting recovery. The method of the invention has a good adaptability and is easy to be realized in a real project.

Description

A kind of coloured image vignetting restored method based on illumination surface modeling
Technical field
The invention belongs to Computer Image Processing field, relate to a kind of vignetting restored method of coloured image.
Background technology
Camera, when remote imaging, along with the increase of field angle, can will reduce by the skew ray area of beam area of photographic lens imaging gradually, and this can cause image bright in the middle of occurring, the phenomenon that edge is dark, Here it is gradual halation phenomena.The existence of gradual halation phenomena can cause image irradiation condition to change, the accuracy rate of target detection, image registration, image co-registration scheduling algorithm is reduced greatly, must be eliminated, vignetting restores the important research content that has become the fields such as remote sensing image processing, computer vision at present, has important Research Significance and actual application value.
Obtaining correct vignetting function is to realize the key that image vignetting restores.Traditional images vignetting restored method normally calculates vignetting function according to relevant optics and geometric parameter, or by related experiment, determines vignetting function in advance, lacks adaptivity, is difficult to realize in Practical Project.Wherein, 1) traditional optics and geometric restitution method have tight theoretical foundation, can obtain vignetting function accurately, but precondition is to understand the correlation technique parameter of camera, and the relevant informations such as distance of camera and target while taking, this is often difficult to realization in Practical Project.2) first the method based on look-up table (LUT) and the matching of lining by line scan need to utilize standard video (as specific pattern on blank sheet of paper) to test, to obtain the table of comparisons that affects coefficient of vignetting, the recycling table of comparisons, carries out vignetting recovery by lining by line scan to image.The method need to utilize standard video to obtain image vignetting function reference table in advance, and simultaneously each shooting all must meet identical condition, and this has also limited its application in Practical Project to a great extent.
Summary of the invention
In order to address the above problem, the present invention proposes a kind of coloured image vignetting restored method based on illumination surface modeling, its objective is without any optics, geometric parameter information, do not need to utilize in advance template to carry out under the condition of related experiment simultaneously yet, only according to the Illumination Distribution of colored vignetting image own, utilize the method for three-dimensional modeling to obtain its vignetting function, thereby realize the automatic recovery of image gradual halation phenomena.
The coloured image vignetting restored method that the present invention proposes, mainly comprises following step:
A coloured image vignetting restored method for illumination surface modeling, mainly comprises following step:
1) original color vignetting image f is transformed into HSI space from rgb space, obtains the image f in H, S, tri-passages of I h, f s, f i; Extract prospect and the background area of vignetting image;
2) utilize coloured image decomposition technique, realize the decomposition of original color vignetting picture structure and texture, obtain its colored structural images f u; By image f ube transformed into HSI space, obtain I channel architecture image I u; At I uin the background area of image, according to homogeneity principle Selection Center point;
3) calculate any two central point p i, p jbetween radial distance
Figure BDA0000138704190000021
1≤i, j≤M, wherein || || represent Euclidean distance, M represents central point sum;
4) calculate I channel architecture image I uat each central point p ithe pixel value I at place i; According to formula
Figure BDA0000138704190000022
calculating parameter c i, 1≤i≤M; If certain treats that modeling point is for (x, y), calculate and treat modeling point (x, y) and each central point p ibetween radial distance, d i(x, y), 1≤i≤M, according to formula calculate the pixel value after this dot image modeling; Repeat above-mentioned steps, complete the modeling for the treatment of modeling point to all, obtain the curved surface I ' after modeling;
5) using I ' that modeling obtains as vignetting function, utilize itself and original image f i, and normal illumination surface f irelation between ' three: f i'=f i/ I ', recovers the original vignetting image of I passage f inormal illumination surface f i'; Utilize the illumination surface f after recovering ithe original vignetting image of ' replacement I passage f i, the original image f in H, S Color Channel h, f sconstant, image is transformed into rgb space from HIS space, obtain the coloured image after vignetting restores.
The present invention is before carrying out modeling to image illumination surface, and the method for first utilizing coloured image to decompose extracts the structural information of original color image, realizes the smothing filtering of protecting edge, makes image illumination surface meet the requirement of whole flatness; This measure can effectively reduce the conditional number of solution matrix, improves the accuracy of image modeling.By modeling is carried out in original color vignetting image illumination surface, the vignetting function of picture of can direct estimation publishing picture, and then realize the automatic recovery of image gradual halation phenomena; Because the present invention is without any need for optics, and geometric parameter information during photograph taking, do not need to utilize in advance template to carry out related experiment yet, therefore there is good adaptivity, in Practical Project, be easy to realize.
Accompanying drawing explanation
Fig. 1 is the coloured image vignetting restored method theory diagram based on illumination surface modeling.
Fig. 2 has provided coloured image modeling and vignetting recovery effect.Wherein, Fig. 2 (a) is original color vignetting image; The structural images of Fig. 2 (b) for utilizing coloured image decomposition technique to obtain; Fig. 2 (c) is vignetting display foreground extracted region effect; The relevant central point of Fig. 2 (d) for choosing, wherein " o " represents central point position; Fig. 2 (e) and Fig. 2 (f) are respectively the illumination surface three-dimensional distribution map before and after colored vignetting structural images I component modeling; Fig. 2 (g) and Fig. 2 (h) are respectively the illumination surface energy profile before and after colored vignetting structural images I component modeling; The vignetting recovery effect figure that Fig. 2 (i) utilizes the inventive method to obtain.
Embodiment:
As everyone knows, under identical illumination condition, Illumination Distribution in identical texture region should meet the feature of asymptotic variation, yet real image is comprised of different texture mostly, due to the difference of reflection coefficient, even under identical illumination condition, the illumination surface distributed of different texture also can distort, therefore can not be by modeling be carried out in whole image illumination surface, and the global illumination that obtains image distributes.
It should be noted that, nearly all natural image is all comprised of prospect and background area, foreground area how complicated no matter, but its background area is comprised of single texture often, that is to say, the Illumination Distribution in most of image background regions can both meet the feature of asymptotic variation.Therefore, the present invention intends choosing relevant central point from having in the background area of identical texture, and utilizes above-mentioned central point to carry out modeling to integral image Illumination Distribution, and then obtains the whole vignetting function of image, to realize the recovery of image gradual halation phenomena.At present existing several different methods can realize effective extraction in display foreground region, in the present invention, repeats no more.Below the present invention is described in detail.
1, coloured image decomposes
The object that coloured image decomposes is from original color image, to extract its structural images and texture image, the former mainly comprises the low-frequency information of image, can realize the smothing filtering of protecting edge, the latter mainly comprises the high-frequency informations such as details of image, be that original image f can be decomposed into structure division u and texture part v, and meet and be related to f=u+v.Coloured image decomposes can adopt several different methods, if document [1] is (referring to Luminita A.Vese, Stanley J.Osher. " Color texture modeling and color image decomposition in a variational-PDE approach, " Proceedings of the Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC ' 06), 2006, pp.103-110.) point out, from original image f, extract its structural images u, can be regarded as a function minimization problem with fixed boundary, its energy functional minimum model can be expressed as:
inf u , g 1 , g 2 { ∫ | ▿ u | + λ ∫ | f - u - ∂ x g 1 - ∂ x g 2 | 2 dxdy + μ [ ∫ ( g 1 2 + g 2 2 ) p dxdy ] 1 p } - - - ( 1 )
Wherein, λ, μ, p is prior selected correlation parameter, inf{} representative makes function { } reach minimum value,
Figure BDA0000138704190000032
Figure BDA0000138704190000033
conversion vector, u x, u ythe single order local derviation of difference representative structure image to ranks coordinate, the gradient of representative structure image.
By formula (1) respectively to u, g 1, g 2ask local derviation, can obtain relevant Euler-Lagrange equation.Utilize alternative manner to solve, just can obtain structural images u.At tri-color spaces of RGB, repeat aforesaid operations, can realize the automatic classifying of coloured image.
Document [2] (can be referring to Jean-Francois Aujol, Sung Ha Kang. " Color image decomposition and restoration. " Journal of Visual Communication and Image Representation, 2006,17 (4), pp:916-928.) be to carry out picture breakdown according to the brightness of image and colourity, be about to structural images u and be divided into colourity u cwith brightness u btwo parts, and meet and be related to u=u c* u b; In like manner, there is f=f c* f b, v=v c* v b, f=u+v, f wherein, v represents respectively original image and texture image; Can be according to minimum model
Figure BDA0000138704190000035
solve structural images u, wherein
Figure BDA0000138704190000036
r, g, b is the RGB passage of representative image respectively,
Figure BDA0000138704190000037
the gradient of representative structure image; Recycling is related to that v=f-u solves texture image v, can realize the automatic classifying of coloured image.
The method that the present embodiment adopts document [1] to provide is carried out the automatic classifying of colored vignetting image.In the present invention, iteration initial value is made as respectively u 0=.f,
Figure BDA0000138704190000041
wherein f is original image, f x, f ythe single order local derviation of difference representative image to ranks coordinate,
Figure BDA0000138704190000043
the gradient of representative image.Related parameter choosing is λ=0.01, μ=0.2, p=1; Inventor's research in earlier stage shows, chooses above-mentioned parameter and can realize to a great extent the smothing filtering that image is protected edge, reduces noise and additional interference as far as possible, improves modeling effect.
2, image illumination surface modeling
In recent years, the method based on radial basis function has been widely used in the three-dimensional modeling of the smooth energy field such as light stream, energy distribution, electromagnetic field or smooth surface.The present invention is incorporated into image processing field by above-mentioned model, and has carried out corresponding improvement.Different from traditional light stream or energy field distribution, the illumination curved surface fluctuation of real image surface is violent, cannot meet the requirement of whole flatness, can not utilize classic method directly image to be carried out to modeling.In order to address the above problem, before modeling is carried out in image illumination surface, the method [1] that first the present invention utilizes coloured image to decompose extracts the structural information of original color image, realizes the smothing filtering of protecting edge, makes image illumination surface meet the requirement of whole flatness; This measure can effectively reduce the conditional number of solution matrix, improves the accuracy of image modeling.
If integral image region is modeling region Ω, on Ω, choose equably N * N point, remove the point in foreground area, remaining point is designated as to central point p k, 1≤k≤M, the central point that utilization is chosen, imaging surface illumination is carried out to modeling, concrete grammar can be referring to ([3] L.Ling and E.J.Kansa, " A least-squares preconditioner for radial basis functions collocation methods, " Advances in Computational Mathematics, vol.23, pp.31-54, 2005.) or ([4] Y.Duan, P.F.Tang, T.Z.Huang and S.J.Lai, " Coupling projection domain decomposition method and Kansa ' s method in elcectrostatic problems, " Computer physics Communications, vol.180, pp.209-214, 2009.) the present invention adopts the image function value at each point place after the method computation modeling that document [4] provides.Take gray level image as example, and concrete steps are as follows:
1) utilize picture breakdown technology, realize the automatic classifying of original image structure and texture, obtain its structural images I u, in its known region, according to homogeneity principle Selection Center point;
2) calculate any two central point p i, p jbetween radial distance
Figure BDA0000138704190000044
1≤i, j≤M, wherein || || represent Euclidean distance, M represents central point sum;
3) computation structure image I uat each central point p ithe pixel value I at place i; According to formula
Figure BDA0000138704190000045
calculating parameter c i, 1≤i≤M;
4) calculate and treat modeling point (x, y) and each central point p ibetween radial distance, d i(x, y), 1≤i≤M, according to formula
Figure BDA0000138704190000051
the pixel value I ' (x, y) that after computed image modeling, point (x, y) is located;
5) repeat above-mentioned steps, complete to modeling a little, obtain the curved surface I ' after modeling.
3, vignetting restores
The vignetting model providing according to Kang Weiss, vignetting image f ' (x, y) can be expressed as: f ' (x, y)=f (x, y) * I (x, y), wherein f (x, y) represents original image, I (x, y) represents vignetting function.Therefore, obtain after vignetting function I (x, y), only need utilize to be related to and can to recover original image by f (x, y)=f ' (x, y)/I (x, y), thereby realize the removal of gradual halation phenomena.
In the present invention, we only carry out modeling to image I passage, utilize the illumination surface f after recovering ithe original vignetting image of ' replacement I passage f i, the original image f in H, S Color Channel h, f sconstant; Recycling color of image space conversion formula, is transformed into rgb space by image from HIS space, can obtain the coloured image after vignetting restores.
From Fig. 2 (b), can find out, compare with original graph 2 (a), after coloured image resolution process, image has been realized level and smooth significantly under the former marginate condition of maintenance, the flatness requirement of effects on surface illumination while having guaranteed image modeling, effectively remove additional noise and interference, improved modeling effect.
From Fig. 2 (f) and Fig. 2 (h), can find out, utilize background area to carry out after modeling image, integral image illumination patterns presents the trend of asymptotic variation, and consistent with traditional vignetting illumination patterns model, and middle high, edge is low; Therefore can be used for reflecting the illumination patterns of integral image.From Fig. 2 (i), can find out, utilize method of the present invention, the gradual halation phenomena of image has obtained effective inhibition, has obtained gratifying result.

Claims (1)

1. the coloured image vignetting restored method based on illumination surface modeling, mainly comprises following step:
1) original color vignetting image f is transformed into HSI space from rgb space, obtains the image f in H, S, tri-passages of I h, f s, f i; Extract prospect and the background area of original color vignetting image f;
2) utilize coloured image decomposition technique, realize the decomposition of original color vignetting image f structure and texture, obtain its colored structural images f u; By colored structural images f ube transformed into HSI space, obtain I channel architecture image I u; In I channel architecture image I ubackground area in, according to homogeneity principle Selection Center point;
3) calculate any two central point p i, p jbetween radial distance wherein || || represent Euclidean distance, M represents central point sum;
4) calculate I channel architecture image I uat each central point p ithe pixel value I at place i; According to formula
Figure FDA0000414379400000012
calculating parameter c i, 1≤i≤M; If certain treats that modeling point is for (x, y), calculate and treat modeling point (x, y) and each central point p ibetween radial distance, d i(x, y), 1≤i≤M, according to formula
Figure FDA0000414379400000013
calculate this pixel value after the modeling of modeling dot image; Repeat above-mentioned steps, complete the modeling for the treatment of modeling point to all, obtain the curved surface I ' after modeling;
5) using I ' that modeling obtains as vignetting function, utilize itself and original image f i, and normal illumination surface f irelation between ' three: f i'=f i/ I', recovers the original vignetting image of I passage f inormal illumination surface f i'; Utilize the illumination surface f after recovering ithe original vignetting image of ' replacement I passage f i, the original image f in H, S Color Channel h, f sconstant, image is transformed into rgb space from HIS space, obtain the coloured image after vignetting restores.
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