自适应非局部3维全变分彩色图像去噪  

Color image denoising using adaptive non-local 3D total variation

作　　者：李潇瑶 王炼红[1] 周怡聪 章兢[1] Li Xiaoyao;Wang Lianhong;Zhou Yicong;Zhang Jing(College of Electrical and Information Engineering,Hunan University,Changsha 410082,China;Department of Computer and Information Science,University of Macao,Macao 999078,China)

机构地区：[1]湖南大学电气与信息工程学院,长沙410082 [2]澳门大学电脑与资讯科学系,中国澳门999078

出　　处：《中国图象图形学报》2022年第12期3450-3460,共11页Journal of Image and Graphics

基　　金：国家重点研发计划资助(2019YFE0105300);国家自然科学基金项目(61573299);中国高校产学研创新基金重点项目(2019ITA01016)。

摘　　要：目的许多彩色图像去噪算法未充分利用图像局部和非局部的相似性信息,并且忽略了真实噪声在彩色图像不同区域内分布的差异,对不同图像块和不同颜色通道都进行同等处理,导致去噪图像中同时出现过平滑和欠平滑现象。针对这些问题,本文提出一种自适应非局部3维全变分去噪算法。方法利用一个非局部3维全变分正则项获取彩色图像块内和块间的相似性信息,同时在优化模型的保真项内嵌入一个自适应权重矩阵,该权重矩阵可以根据每次迭代得到的中间去噪结果的剩余噪声来调整算法在每个图像块、每个颜色分量以及每次迭代中的去噪强度。结果通过不同的高斯噪声添加方式得到两个彩色噪声图像数据集。将本文算法与其他6个基于全变分的算法进行比较,采用峰值信噪比(peak signal-to-noise ratio,PSNR)和结构相似性(structural similarity,SSIM)作为客观评价指标。相比于对比算法,本文算法在两个噪声图像数据集上的平均PSNR和SSIM分别提高了0.16~1.76 dB和0.12%~6.13%,并获得了更好的图像视觉效果。结论本文去噪算法不仅更好地兼顾了去噪与保边功能,而且提升了稳定性和鲁棒性,显示了在实际图像去噪中的应用潜力。Objective Images are often distorted by noise during image acquisition,transmission and storage process.The generated noise can degrade image quality and affect image processing,such as edge detection,image segmentation,image recognition and image classification.Image denoising technique plays a key role in image pre-processing for image details preservation.Current Gaussian noise removal denoising techniques is often based on variational model like the total variation(TV)method.It can realize image smoothing through minimizing the corresponding energy function.However,TV-based denoising methods have their staircase effects and detail loss due to local gradient information only.Many researchers integrate the non-local concept into the total variation model after the non-local means was proposed.The existing non-local TV-based methods take advantages of the non-local similarity to denoise the image while keeping the image structure information.Unfortunately,many existing TV-based color image denoising methods fail to fully capture both local and non-local correlations among different image patches,and ignore the fact that the realistic noise varies in different image patches and different color channels.These always lead to over-smoothing and under-smoothing in the denoising result.Our newly TV-based color image denoising method,named adaptive non-local 3 D total variation(ANL3 DTV),is developed to deal with that.Method 1)Decompose the noisy color image into K overlapping color image patches,search for the m most similar neighboring image patches to each center image patch and then group the m image patches together.2)Vectorize every color image patch in each image patch group and stack them into a 2 D noisy matrix.3)Obtain the corresponding 2 D denoised matrices via ANL3 DTV.To get the inter-patch and intra-patch correlations,our ANL3 DTV takes advantages of a non-local 3 D total variation regularization.On the basis of embedding an adaptive weight matrix into the fidelity term of the optimization model,it can au

关 键 词：彩色图像去噪 高斯噪声 非局部相似性 3维全变分 自适应权重 

分 类 号：TN911.73[电子电信—通信与信息系统]