自适应饱和度–明度全变差的彩色图像去噪算法
A Color Image Denoising Algorithm with Adaptive Saturation-Value Total Variation
摘要: 基于饱和度–明度全变差的图像去噪模型(SV-TV模型)能有效去除彩色图像中的高斯噪声，但去噪效果依赖于模型中正则化参数的选取。本文在SV-TV模型的基础上，结合交替迭代极小化方法，提出一种自适应饱和度–明度全变差的彩色图像去噪算法。该算法利用广义交叉验证技术，使得SV-TV模型中的正则化参数在算法迭代过程中可以自动更新。数值实验结果验证了所提自适应算法的有效性与可行性。
Abstract: Saturation-value total variation (SV-TV) model can effectively remove Gaussian noise in color imag-es, and its denoising effect depends on the selection of regularization parameters. Based on the SV-TV model, this article proposes an adaptive color image denoising algorithm by using the alter-nating minimization method. The algorithm utilizes the generalized cross-validation technique to automatically update the regularization parameters in the SV-TV model. Numerical experimental results validate the effectiveness and feasibility of the proposed adaptive algorithm.
文章引用：仇扬. 自适应饱和度–明度全变差的彩色图像去噪算法[J]. 应用数学进展, 2023, 12(11): 4601-4616. https://doi.org/10.12677/AAM.2023.1211451

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