摘要
三维块匹配(BM3D)算法能够有效抑制平稳信号中的噪声。对于具有随机特性的合成孔径雷达影像斑点噪声,受限于三维变换阈值单一和在局部邻域寻找相似块,BM3D算法的滤波效果不佳。提出了基于K-Means聚类的BM3D算法,并将其应用于合成孔径雷达影像斑点噪声抑制。对图像块集合根据均值、方差和极差值构建的特征向量进行聚类,估计每一类块的噪声方差,根据类噪声方差估计自适应三维变换阈值;在每一个图像块类内部寻找相似块,实现全局相似块的快速查找。实验结果表明,同BM3D算法和非局部均值算法相比,所提算法具有更好的视觉效果和更高的峰值信噪比。
Three-dimensional block-matching （BM3D） algorithm can effectively suppress the noise in stationary signal. However, it is not feasible for the speckle noise in synthetic aperture radar （SAR） image with random characteristics due to the single 3D transform threshold and the local neighborhood for searching similar blocks. We propose a BM3D algorithm based on K-Mean clustering for SAR image denoising. First, we calculate the feature vector according to the mean, variance, and poor value, and estimate noise variance of each image block. The adaptive 3D transform threshold will be determined through the estimated noise variance. Second, we can find similar image blocks of reference image block in the corresponding class of image blocks, and can find global similar image blocks quickly. The experiments demonstrate that the proposed algorithm achieves better visual effect and and higher peak signal to noise ratio than the BM3D algorithm and non-local mean algorithm.
作者
詹云军
代腾达
黄解军
董玉森
叶发旺
唐聪
王萌
Zhan Yunjun;Dai Tengda;Huang Jiejun;Dong Tang Cong;Wang Meng(School of Resources and Environmental Engineering, Wuhan Wuhan, Hubei 430070, China;Yusen2 , Ye Fawang3 , University of Technology z School of Earth Sciences, China University of Geosciences, Wuhan, Hubei 430074, China;National Key Laboratory of Remote Sensing Information and Image Analysis Technology, CNNC Beijing Research Institute of Uranium Geology, Beijing 100029, China)
出处
《激光与光电子学进展》
CSCD
北大核心
2018年第4期115-121,共7页
Laser & Optoelectronics Progress
基金
国家自然科学基金(41571514)
中核集团自主研发项目(遥HXY111-1)
中科院生态所委托项目(20151h0047)
关键词
图像处理
合成孔径雷达
斑点噪声抑制
三维块匹配
图像块聚类
自适应阈值
image processing
synthetic aperture radar
speckle noise suppression
three-dimensional block-matching
image block clustering
adaptive threshold
