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Interactive grayscale image colorizing method based on local linear model optimization

A local linear, grayscale image technology, applied in image data processing, 2D image generation, filling planes with attributes, etc., can solve problems such as dependence on similarity, color penetration, easy color penetration, etc.

Inactive Publication Date: 2012-11-14
WENZHOU UNIVERSITY
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

But it only reduces the color bleeding phenomenon compared to the algorithm of Levin et al., and the algorithm of Bhat et al. relies on edge detection. When the edge is not obvious or closed, it is easy to color bleeding phenomenon. See Bhat, Pravin and Zitnick, C . Lawrence and Cohen, Michael and Curless, Brian. GradientShop: A gradient-domain optimization framework for image and video filtering. ACM Transactions on Graphics, 2010, 29(2): 10: 1-10: 14
The effect of the colorization method based on the color transfer method is strongly dependent on the similarity between the reference image and the target image, and it is difficult to select a suitable reference image. However, the existing image colorization based on local color expansion is simple to operate. , convenient, but in the case of a small number of users coloring, the phenomenon of color bleeding is still serious

Method used

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  • Interactive grayscale image colorizing method based on local linear model optimization
  • Interactive grayscale image colorizing method based on local linear model optimization
  • Interactive grayscale image colorizing method based on local linear model optimization

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Embodiment 1

[0068] Such as figure 1 As shown, the interactive grayscale image colorization method based on local linear model optimization described in this embodiment includes the following six steps:

[0069] (1) Input the grayscale image to be processed, then convert the grayscale image to be processed into RGB color space, and the generated image is used as the input image;

[0070] (2) Carry out artificial line coloring to the input image in step (1), obtain the coloring image;

[0071] (3) Convert the RGB color space of the input image and the coloring image to the YUV color space respectively, obtain the luminance component Y, the chroma component U and the chroma component V of the image after conversion, and mark the luminance component of the input image at YUV as I , the shaded image has a YUV chroma component of S U and S V , S U and S V is an N×1 matrix, and N is the product of the length and width of the image;

[0072] The conversion method that described is converted...

Embodiment 2

[0139] The interactive grayscale image colorization method based on local linear model optimization described in this embodiment is different from Embodiment 1 in that in step (4), the Laplacian matting matrix is ​​calculated according to the following formula:

[0140]

[0141] In the formula:

[0142] i, j and k are image pixel index values;

[0143] The matting Laplacian matrix L is an N×N matrix;

[0144] N is the product of the length and width of the image;

[0145] δ ij is the Kronecker function, if i and j are equal, then δ ij is 1, otherwise δ ij is 0;

[0146] mu k and are the ω centered at k in the luminance component I, respectively k The mean and variance of the pixels in the window, in this method ω k Use a 3×3 window;

[0147] |ω k |Indicates the number of pixels in the window;

[0148] ∈ is the regularization parameter;

[0149] I is the brightness component of input image in YUV in step (3);

[0150] D. t is the diffusion distance, solved by...

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Abstract

The invention discloses an interactive grayscale image colorizing method based on local linear model optimization. The method includes: inputting a grayscale image to be processed, converting the grayscale image to be processed into a red, green and blue (RGB) color space input image, conducting a little manual line coloring to obtain a colorized image, converting the grayscale image to be processed and the colorized image to a YUV color space from an original RGB color space respectively, calculating a laplace sectional drawing matrix, optimizing and solving a sparse matrix equation by using a local linear model, obtaining the colorized image based on the YUV color space, and finally converting the colorized image based on the YUV color space into the RGB color space to obtain a final colorized image. The method improves an existing image colorizing method based on local color expansion, reduces severe color permeation problems occurring in a grayscale image colorization process under the condition of less manual line coloring, and improves grayscale image colorization quality.

Description

technical field [0001] The invention relates to a grayscale image colorization method, in particular to an interactive grayscale image colorization method based on local linear model optimization. Background technique [0002] Colorization is the process of adding color to a black-and-white image, movie, or TV show. Traditional black-and-white image colorization technology is done purely manually or with the assistance of computer software tools, and this work requires a lot of time. Because colorization technology has considerable practical application value, it is widely used in many fields such as image, video editing and image communication, as well as science, industry and military. Colorization is the process of calculating the color components given the brightness components of the image, so it can be regarded as a pathological problem. According to the regularization form for dealing with ill-conditioned problems, colorization can be divided into two types of proce...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T11/00G06T11/40
Inventor 厉旭杰赵汉理黄辉
Owner WENZHOU UNIVERSITY
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