A Coupled Non-local Total Variation Algorithm for Image Colorization
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摘要: 基于局部算子的全变差(TV)模型在对纹理图像着色时，会出现颜色扩散不均匀，着色范围区域较小等问题。为了解决上述问题，该文提出基于非局部算子的耦合全变差图像着色模型，结合交替方向乘子法(ADMM)，设计出相应的数值求解算法，并给出该算法的收敛性结果。该模型充分利用像素邻域亮度之间的相似性进行颜色扩散，能有效避免仅利用亮度边缘信息进行局部扩散导致颜色扩散不均匀的问题。数值实验结果表明，该模型在快速着色的同时，能有效解决颜色在纹理等细节处扩散不均匀的问题。Abstract: The traditional Total Variation (TV) model based on local operators for texture image colorization has some problems, such as inhomogeneous color diffusion, small coloring ranges and so on. In order to solve these problems, a coupled total variation model based on nonlocal operators is presented for image colorization, and the correspond numerical algorithm is designed to solve the model by incorporating the Alternating Direction Method of Multipliers (ADMM), and the convergence result of the algorithm is given. The proposed model makes full use of the similarity between the brightness of the pixel areas to perform color diffusion, which can effectively avoid the problem of inhomogeneous color diffusion due to local diffusion only using the brightness edge information. The experimental results are given to show that the model can effectively solve the problem of inhomogeneous color diffusion at textures and other details while fast colorizing.
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表 2 图3图像着色后的PSNR值及MSE值的比较
图像 模型 PSNR值 MSE值 第1排 Levin模型[4] 23.69 0.0043 Kang模型[8] 22.74 0.0053 金模型[9] 25.46 0.0028 本文模型 25.82 0.0026 第2排 Levin模型[4] 24.63 0.0034 Kang模型[8] 22.10 0.0062 金模型[9] 27.52 0.0018 本文模型 26.91 0.0020 第3排 Levin模型[4] 24.87 0.0033 Kang模型[8] 21.71 0.0067 金模型[9] 25.21 0.0030 本文模型 26.04 0.0025 第4排 Levin模型[4] 24.85 0.0033 Kang模型[8] 21.04 0.0079 金模型[9] 25.66 0.0027 本文模型 25.87 0.0026 
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