基于分数阶全变分和低秩正则化的彩色图像去模糊方法  

Color Image Deblurring Based on Fractional Total Variation and Low-Rank Regularization

作　　者：马飞[1] 王梓璇 杨飞霞[2] 徐光宪[1] MA Fei;WANG Zixuan;YANG Feixia;XU Guangxian(Liaoning Technical University,School of Electronic and Information Engineering,Huludao 125000,China;Liaoning Technical University,School of Electrical and Control Engineering,Huludao 125000,China)

机构地区：[1]辽宁工程技术大学,电子与信息工程学院,辽宁葫芦岛125000 [2]辽宁工程技术大学,电气与控制工程学院,辽宁葫芦岛125000

出　　处：《电光与控制》2024年第5期101-107,共7页Electronics Optics & Control

基　　金：国家自然科学基金(61971210);辽宁省自然科学基金(2023-MS-314);辽宁省教育厅科学研究基金(LJKZ0357)。

摘　　要：针对现有的彩色图像去模糊过程中存在色彩失衡、阶梯效应和伪影等现象,提出了一种基于分数阶全变分和低秩正则的图像去模糊优化方法。首先,将传统的RGB彩色图像转换到YCbCr颜色空间,利用其亮度通道特征解决色彩失衡问题;其次,利用分数阶全变分的特征消除图像恢复任务中出现的阶梯效应,并且引入加权核范数低秩正则进一步抑制伪影及噪声;最后,利用交替方向乘子法设计出高效的求解方法,通过迭代优化得到纯净图像的最优估计。对彩色图像测试的实验结果表明,所提出的方法对图像去模糊任务取得较好的视觉恢复效果,客观评价指标良好。In the existing color image deblurring process,there are such phenomena as color imbalance,step effect and artifacts.To solve the problems,an image deblurring optimization method based on fractional total variation and low-rank regularization is proposed.Firstly,the color image in traditional RGB space is converted to YCbCr color space,and its luminance channel characteristics are used to solve the problem of color imbalance.Secondly,fractional total variation characteristics are used to eliminate step effect in image recovery tasks.Moreover,the weighted kernel norm low-rank regularization is introduced to further suppress artifacts and noise.Finally,the Alternating Direction Method of Multipliers(ADMM)is used to design an efficient solving method,and the optimal estimation of the clear image is obtained through iterative optimization.The experimental results of color image testing show that the proposed method exhibits fine performance in image deblurring tasks in terms of both visual recovery effects and objective evaluation indexes.

关 键 词：彩色图像去模糊 分数阶全变分 低秩 YCBCR颜色空间 交替方向乘子法 

分 类 号：TP317.4[自动化与计算机技术—计算机软件与理论]