CN102663788B - Pen light-colored artistic effect drawing method based on unreality feeling - Google Patents

Abstract

The invention relates to a pen light-colored artistic effect drawing method based on unreality feeling, belonging to the technical field of information. The method provided by the invention comprises the following steps: obtaining gradient information of an original image, using DoG filter to filter the gradient information along the gradient direction, and obtaining an edge image of the original image through comparison with a threshold valve; computing linear filtering coefficient through variance and mean value of a local window, performing linear filtering on the original image and then performing abstraction through bilateral filtering to obtain color diffusion effect; overlaying the edge image and an color diffusion image to obtain preliminary pen line effect; adopting a light illumination module to transmit color so as to obtain color information of the original image; and enhancing contrast of the image through a contrast enhancing method so as to obtain final pen light-colored artistic effect. The advantages of the method provided by the invention are as follows: the pen light-colored artistic effect drawing method more conforms with aesthetic standard of people, has fast processing speed, good flexibility and wide application scope and is beneficial complementation for imitations of different artistic effects based on the unreality feeling.

Description

The light color artistic effect method for drafting of a kind of pen based on feeling of unreality

Technical field:

The invention discloses the light color artistic effect method for drafting of a kind of pen based on feeling of unreality, relate to the analog simulation method for drafting of the light color artistic effect of pen in computer graphic image processing, belong to areas of information technology.

Background technology:

Along with improving constantly of scientific and technological progress and people's esthetic sentiment, non-photorealistic rendering technology (Non-Photorealistic Rendering) has obtained people's extensive attention, be prevalent in the fields such as films and television programs, advertising, sight spot roaming, Entertainment, institute's role is more and more outstanding.Non-photorealistic rendering is paid attention to the Freehandhand-drawing art feature of graph image, and style is versatile and flexible, and the main target of its drafting often does not need to show the sense of reality of figure, and mainly gives prominence to some artistic speciality of main body in figure.

Non-photorealistic rendering technology stresses to simulate the artistic work with various different-styles, as style works such as oil painting, watercolor, pencil drawing, abstract paintings, the artistic style works that have in reality are too numerous to mention, utilize the light color artistic style works of the coloured pen-and-ink drawing of Computer Simulation tool, being that the useful of non-photorealistic rendering effect supplemented, is an important technology of feeling of unreality art speciality simulation.In known technology, Liu Yingqin (< Shandong Normal University Master's thesis, 2010>) adopts image segmentation technique that still image is played up to the artistic effect into cartoon style; Han Bo (< Xi'an Technology University Master's thesis, 2011>) is studied the color transmission of feeling of unreality, has proposed color transmission Indexes of Evaluation Effect; Kang Lifeng (< Liaoning Normal University Master's thesis, 2009>) is the artistic effect image with watercolor style by the two-dimensional static image processing of input; Zhao Binru (< University of Electronic Science and Technology Master's thesis, 2009>) based on optical illumination model realization the feeling of unreality effect of cartoon style and the stylization of black and white pen, pen-and-ink drawing style adopts profile to extract, and shading and texture synthesis method have been realized monochromatic tree-like trunk; Ai Lichao (< South China Science & Engineering University Master's thesis, 2010>) has designed cartoon style artistic style rendering system; Niu Xiaodong (< Sichuan Teachers University Master's thesis, 2011>) has designed the drawing system of ink and wash style; Money Wenhua (< Yunnan University PhD dissertation, 2010>) has designed the rendering system of pencil drawing, fluid artistic style style; Huang Hua etc. (< Chinese journal of computers >, 2009,32 (10): 2023-2030) have realized real-time sketch stylization artistic effect; Xiao Fu etc. (< Journal of Image and Graphics >, 2009,14 (4): 738-744) simulation has generated the feeling of unreality art image of lines fluctuations, the artistic feeling virtual environment that formation can be roamed; Min Feng etc. (< Journal of Image and Graphics >, 2009,32 (8): 1595-1602) adopt with or figure generate and there is the portrait painting artistic effect of multiple style; The thing people wait (< patent CN200810114120.9>, 2008) to simulate the rule of painter based on water flow structure figure recklessly, automatically generate Chinese ink painting; Huang Hua etc. (< patent CN200910023002.1>, 2009), according to the feature of sketch and human eye vision, generate the artistic effect of sketch stylization; Li Yun sunset etc. (< patent CN2001110210312.1>, 2011) disclose a kind of generation method and system of computer sketch images; Liu Hao etc. (< patent CN200510121488.4>, 2005) have proposed a kind of interactive ink and wash style real-time 3 D romance and real-time animation rendering intent.

Relatively known computing machine pen artistic effect analogy method, the present invention, taking linear filter technology as basis, proposes the light color artistic effect method for drafting of a kind of pen based on feeling of unreality.By literature search, have no the open report identical with the present invention.

Summary of the invention:

The object of the present invention is to provide the more realistic situation of one, have more the light color artistic effect method for drafting of the pen based on feeling of unreality of general and versatility.

The present invention is taking linear filtering as core, there is colored pen-and-ink drawing artistic effect as starting point to produce, still image to input is processed, provide the method for input picture being carried out to DoG edge extracting and obtains pen profile, method with linear filtering and the light color effect of abstract treatment of simulated has been proposed, and color transmission method based on optical illumination model.

The present invention completes according to the following steps:

The light color artistic effect method for drafting of pen technological process based on feeling of unreality is: first, ask for the gradient information of original image, use DoG wave filter to carry out filtering processing along gradient direction, by with the edge image of relatively asking for original image of threshold value; Then, adopt variance and the mean value computation linear filtering coefficient of local window, and original image is carried out to linear filtering processing, adopt on this basis bilateral filtering to carry out abstract, obtain color diffusion effect; Then, edge image and color diffusion image are superposeed, obtain preliminary pen lines effect; In order to obtain the color information of original image, adopt optical illumination model to transmit color; Finally, adopt the method for contrast enhancing to strengthen the contrast of image, obtain the light color artistic effect of final pen; Concrete steps are as follows:

(1) DoG edge extracting

Ask for the gradient of input picture Input, use DoG wave filter to carry out filtering along gradient direction, the output of wave filter is amplified along true edge, the response of accumulating each wave filter obtains F (s):

$F\left(s\right)={\&Integral;}_{-T}^T\mathrm{Input}\left(l\left(t\right)\right)f\left(t\right)\mathrm{dt}$

In formula, l (t) is the value of input picture Input on gradient straight line l, and f (t) is the wave filter that adopts Gaussian function.

By F (s) along gradient direction integration to strengthen the continuity of lines, obtain the image A (x) that lines strengthen:

$A\left(x\right)={\&Integral;}_{-S}^S{G}_{\mathrm{\&sigma;}}\left(s\right)F\left(s\right)\mathrm{ds}$

In formula, G _σ(x) be that standard deviation is the one dimension Gaussian function of σ.

Finally, by A (x) and threshold tau comparison, after binaryzation, obtain the edge image edge of a width black and white:

(2) linear filtering is fuzzy

Input picture Input is adopted to coefficient a _k, b _kcarry out linear filtering, obtain filtering ambiguous result M:

M＝a _kInput+b _k,i∈w _k

$a_k=\frac{\frac{1}{\left|w\right|}{\mathrm{\&Sigma;}}_{i\&Element;w_k}({\mathrm{Input}}_i^2-{\mathrm{\&delta;}}_k\stackrel{\&OverBar;}{{\mathrm{Input}}_k})}{{\mathrm{\&psi;}}_k^2+e}$

$b_k=\stackrel{\&OverBar;}{{\mathrm{Input}}_k}-a_k{\mathrm{\&delta;}}_k$

In formula, δ _kwith for window w _kinterior average and variance, | w| represents window w _kin number of pixels, for input picture Input is at window w _kin average.

(3) abstract processing

Filtering ambiguous result M is converted to LAB color space from rgb color space, adopts the neighborhood Sur that the radius size of Blur is x to pixel location to carry out nonlinear diffusion to luminance channel L, obtain the diffusion result L' of L passage:

$L^{\&prime;}\left(x\right)=\frac{\&Integral;e^{-\frac{1}{2}{\left(\frac{|x-\mathrm{Sur}}{\mathrm{Blur}}\right)}^2}\mathrm{Weight}(\mathrm{Sur},x)*M\left(\mathrm{Sur}\right)\mathrm{dSur}}{\&Integral;e^{-\frac{1}{2}{\left(\frac{|x-\mathrm{Sur}}{\mathrm{Blur}}\right)}^2}\mathrm{Weight}(\mathrm{Sur},x)\mathrm{dSur}}$

In formula, Weight is current pixel and the error amount between neighborhood territory pixel around.Adopt the width interval that parameter is Width to carry out quantification treatment to L', obtain abstract result L ":

In formula, coefficient control quantize number of color number, parameter Q _boundrayit is the marginal information of L'.

By L " be transformed into rgb color space with color channel AB from LAB color space, obtain abstract result image C.

(4) edge strengthens

The edge image edge that abstract result image C is extracted with DoG in proportion coefficient n mixes, and obtains result images G:

G＝n*C+(1-n)*edge 0<n<1

(5) color transmission

Edge is strengthened to the result images G obtaining and adopts optical illumination to depart from the method for mapping, be delivered in result images E with reference to the colouring information of image:

E(i,j)＝H+G(i,j)cos(α)+Kcos ^m(α)

In formula, H parameter is surround lighting, and parameter K and m control the quantity of color transfer, and cos (α) represents to transmit deviation angle, adopts the luminance component of G image to calculate at location of pixels (i, j):

$\cos \mathrm{\&alpha;}(i,j)=\frac{M(i,j)}{255}$

(6) contrast strengthens

Adopt contrast enhancement algorithms to strengthen processing to the result images E of color transmission, obtain the effect image Z that color contrast strengthens:

$Z(x,y)=E(x,y)-\frac{a}{m*n-1}\mathrm{\&Sigma;E}(x^{\&prime;},y^{\&prime;})$

In formula, Z (x, y) is the pixel value at (x, y) some place after contrast strengthens, E (x, y) be the pixel value of image E at (x, y) some place, E (x', y') be pixel (x, y) pixel in neighborhood, m*n is Size of Neighborhood, a is the inhibition strength factor.

Advantage of the present invention and good effect are:

1, utilize computing machine to process input picture, obtain the light color artistic effect of pen of feeling of unreality, on the basis of simple pen artistic effect, given prominence to certain color information, more meet people's aesthetic conceptions.

2, be calculated as basis with DoG edge extracting and linear filtering, compared with known computer drawing feeling of unreality pen-and-ink drawing effect, reduced the drafting time, improved processing speed.

3, carry out color transmission by optical illumination model, and adopt the method that contrast strengthens to change color contrast effect, to meet the demand of different user to color, there is better dirigibility.

4, having set up the method for drafting of the light color effect of a kind of computer simulation feeling of unreality pen, is useful the supplementing of one that feeling of unreality is simulated different artistic effects, has larger potential demand in films and television programs, game movie and advertising field; For the simulation of pen-and-ink drawing artistic work provides a kind of new method for drafting, also for the computer simulation of the different artistic effects such as batik, embroidery, tie dyeing provides strong technical support.

Brief description of the drawings:

Fig. 1 is Technology Roadmap of the present invention.

Fig. 2 is the static colour image of input.

Fig. 3 is the gray level image that original image is converted to.

Fig. 4 is the edge image that gray level image adopts DoG filtering to obtain.

Fig. 5 is the blurred picture that original image linear filtering obtains.

Fig. 6, for blurred picture is transformed into after LAB color space, carries out filtering diffusion and converts back the result images that rgb color space obtains L passage.

Fig. 7 is the RGB result images obtaining after luminance channel being quantized on the basis of filtering diffusion.

Fig. 8 is the fused images obtaining after edge image that the result images that obtains and DoG filtering obtains merges quantizing.

Fig. 9 adopts optical illumination model to carry out the light color effect image of pen obtaining after color transmission on fused images basis.

Figure 10 is the light color effect image of final pen (a=0.6) obtaining after strengthening by contrast.

Figure 11 is the light color effect image of final pen (a=0.3) obtaining after strengthening by contrast.

Figure 12 is the light color effect image of final pen (a=0.8) obtaining after strengthening by contrast.

Embodiment:

The present embodiment is to carry out the light color artistic effect of pen for a secondary static two dimensional image of input to draw, and its concrete steps are as follows:

(1) DoG edge extracting

Input picture Input is converted to gray level image (as Fig. 3), ask for the gradient of gray level image, use DoG wave filter to carry out filtering along gradient direction, the output of wave filter is amplified along true edge, the response of accumulating each wave filter obtains F (s).

$F\left(s\right)={\&Integral;}_{-T}^T\mathrm{Input}\left(l\left(t\right)\right)f\left(t\right)\mathrm{dt}$

In formula, l (t) is the value of input picture Input on gradient straight line l, and f (t) is the wave filter that adopts Gaussian function.

By F (s) along gradient direction integration to strengthen the continuity of lines, obtain the image A (x) that lines strengthen:

$A\left(x\right)={\&Integral;}_{-S}^S{G}_{\mathrm{\&sigma;}}\left(s\right)F\left(s\right)\mathrm{ds}$

In formula, G _σ(x) be that standard deviation is the one dimension Gaussian function of σ, our established standards is poor is 0.7.

Finally, by A (x) and threshold tau comparison:

Threshold tau in formula is empirical value, conventionally adopts 0.3, obtains the outline map edge (as Fig. 4) of a width black and white after binaryzation.

(2) linear filtering is fuzzy

Input picture Input is adopted to coefficient a _k, b _kcarry out linear filtering, obtain filtering ambiguous result image M (as Fig. 5):

M＝a _kInput+b _k,i∈w _k

$a_k=\frac{\frac{1}{\left|w\right|}{\mathrm{\&Sigma;}}_{i\&Element;w_k}({\mathrm{Input}}_i^2-{\mathrm{\&delta;}}_k\stackrel{\&OverBar;}{{\mathrm{Input}}_k})}{{\mathrm{\&psi;}}_k^2+e}$

$b_k=\stackrel{\&OverBar;}{{\mathrm{Input}}_k}-a_k{\mathrm{\&delta;}}_k$

In formula, δ _kwith for window w _kinterior average and variance, window w _ksize be empirical value, w _ksize is got 12*12 conventionally, | w| represents window w _kin number of pixels, for input picture Input is at window w _kin the average of each pixel.

(3) abstract processing

Filtering ambiguous result M is converted to LAB color space from rgb color space, adopt the neighborhood Sur that the radius size of Blur is x to pixel location to carry out nonlinear diffusion to luminance channel L, Blur gets 4.25 conventionally, obtain the diffusion result L' of L passage, L'AB is converted back to rgb color space, obtains spreading result images (as Fig. 6):

$L^{\&prime;}\left(x\right)=\frac{\&Integral;e^{-\frac{1}{2}{\left(\frac{|x-\mathrm{Sur}}{\mathrm{Blur}}\right)}^2}\mathrm{Weight}(\mathrm{Sur},x)*M\left(\mathrm{Sur}\right)\mathrm{dSur}}{\&Integral;e^{-\frac{1}{2}{\left(\frac{|x-\mathrm{Sur}}{\mathrm{Blur}}\right)}^2}\mathrm{Weight}(\mathrm{Sur},x)\mathrm{dSur}}$

Sur in formula gets 5*5 conventionally, and Weight is current pixel and the error amount between neighborhood territory pixel around.

Adopt the width interval that parameter is Width to carry out quantification treatment at LAB color space to L', Width gets 5 conventionally, obtains abstract result L ":

In formula, coefficient control quantize number of color number, our value is 3, parameter Q _boundrayit is the marginal information of L' passage.

By L " be transformed into rgb color space with color channel AB from LAB color space, obtain abstract result image C (as Fig. 7).

(4) edge strengthens

The edge image edge that abstract result image C is extracted with DoG in proportion coefficient n mixes, and obtains result images G (as Fig. 8).

G＝n*C+(1-n)*edge 0<n<1

In formula, scale-up factor n is an empirical value, and we get 0.7 conventionally.

(5) color transmission

Edge is strengthened to the result images G obtaining and adopts optical illumination to depart from the method for mapping, be delivered to (as Fig. 9) in result images E with reference to the colouring information of image:

E(i,j)＝H+G(i,j)cos(α)+Kcos ^m(α)

In formula, deviation angle when cos α represents each pixel transmission, adopts the luminance component of G image to calculate at location of pixels (i, j):

$\cos \mathrm{\&alpha;}(i,j)=\frac{M(i,j)}{255}$

Surround lighting Parameter H in formula we conventionally to get 120, K value be that 0.7, m value is 2.

(6) contrast strengthens

Adopt image contrast to strengthen algorithm the result images E of color transmission strengthened to processing, obtain the effect image Z (as Figure 10) that color contrast strengthens:

$Z(x,y)=E(x,y)-\frac{a}{m*n-1}\mathrm{\&Sigma;E}(x^{\&prime;},y^{\&prime;})$

In formula, Z (x, y) is the pixel value at (x, y) some place after contrast strengthens, E (x, y) be the pixel value of image E at (x, y) some place, E (x', y') be pixel (x, y) pixel in neighborhood, m*n is Size of Neighborhood, our value is 9*9; A is the inhibition strength factor, rule of thumb gets 0.6.

Comprise following six major parts: DoG edge extracting, fuzzy, the abstract processing of linear filtering, edge enhancing, color transmission, contrast strengthen.

Claims (1)

1. the light color artistic effect method for drafting of the pen based on feeling of unreality, is characterized in that the concrete steps of this method for drafting are as follows:

(1) DoG edge extracting

Ask for the gradient of input picture Input, use DoG wave filter to carry out filtering along gradient direction, the output of wave filter is amplified along true edge, the response of accumulating each wave filter obtains F (s):

$F\left(s\right)={\&Integral;}_{-T}^T\mathrm{Input}\left(l\left(t\right)\right)f\left(t\right)\mathrm{dt}$

In formula, l (t) is the value of input picture Input on gradient straight line l, and f (t) is the wave filter that adopts Gaussian function;

By F (s) along gradient direction integration to strengthen the continuity of lines, obtain the image A (x) that lines strengthen:

$A\left(x\right)={\&Integral;}_{-S}^S{G}_{\mathrm{\&sigma;}}\left(s\right)F\left(s\right)\mathrm{ds}$

In formula, G _σ(x) be that standard deviation is the one dimension Gaussian function of σ;

Finally, by A (x) and threshold tau comparison, after binaryzation, obtain the edge image edge of a width black and white:

(2) linear filtering is fuzzy

Input picture Input is adopted to coefficient a _k, b _kcarry out linear filtering, obtain filtering ambiguous result M:

M＝a _kInput+b _k,i∈w _k

$a_k=\frac{\frac{1}{\left|w\right|}{\mathrm{\&Sigma;}}_{i\&Element;w_k}({\mathrm{Input}}_i^2-{\mathrm{\&delta;}}_k\stackrel{\&OverBar;}{{\mathrm{Input}}_k})}{{\mathrm{\&psi;}}_k^2+e}$

$b_k=\stackrel{\&OverBar;}{{\mathrm{Input}}_k}-a_k{\mathrm{\&delta;}}_k$

In formula, δ _kwith for window w _kinterior average and variance, | w| represents window w _kin number of pixels, for input picture Input is at window w _kin average;

(3) abstract processing

Filtering ambiguous result M is converted to LAB color space from rgb color space, adopts the neighborhood Sur that the radius size of Blur is x to pixel location to carry out nonlinear diffusion to luminance channel L, obtain the diffusion result L' of L passage:

$L^{\&prime;}\left(x\right)=\frac{\&Integral;e^{-\frac{1}{2}{\left(\frac{|x-\mathrm{Sur}}{\mathrm{Blur}}\right)}^2}\mathrm{Weight}(\mathrm{Sur},x)*M\left(\mathrm{Sur}\right)\mathrm{dSur}}{\&Integral;e^{-\frac{1}{2}{\left(\frac{|x-\mathrm{Sur}}{\mathrm{Blur}}\right)}^2}\mathrm{Weight}(\mathrm{Sur},x)\mathrm{dSur}}$

In formula, Weight is current pixel and the error amount between neighborhood territory pixel around; Adopt the width interval that parameter is Width to carry out quantification treatment to L', obtain abstract result L ":

In formula, coefficient control quantize number of color number, parameter Q _boundrayit is the marginal information of L';

By L " be transformed into rgb color space with color channel AB from LAB color space, obtain abstract result image C;

(4) edge strengthens

The edge image edge that abstract result image C is extracted with DoG in proportion coefficient n mixes, and obtains result images G:

G＝n*C+(1-n)*edge 0<n<1；

(5) color transmission

Edge is strengthened to the result images G obtaining and adopts optical illumination to depart from the method for mapping, be delivered in result images E with reference to the colouring information of image:

E(i,j)＝H+G(i,j)cos(α)+Kcos ^m(α)

In formula, H parameter is surround lighting, and parameter K and m control the quantity of color transfer, and cos α represents to transmit deviation angle, adopts the luminance component of G image to calculate at location of pixels (i, j):

$\cos \mathrm{\&alpha;}(i,j)=\frac{M(i,j)}{255};$

(6) contrast strengthens

Adopt contrast enhancement algorithms to strengthen processing to the result images E of color transmission, obtain the effect image Z that color contrast strengthens:

$Z(x,y)=E(x,y)-\frac{a}{m*n-1}\mathrm{\&Sigma;E}(x^{\&prime;},y^{\&prime;})$

In formula, Z (x, y) is the pixel value at (x, y) some place after contrast strengthens, E (x, y) be the pixel value of image E at (x, y) some place, E (x', y') be pixel (x, y) pixel in neighborhood, m*n is Size of Neighborhood, a is the inhibition strength factor.