基于Fuzzy-Shrink算法改进的图像去噪方法  

Image denoising based on the improved Fuzzy-Shrink algorithm

作　　者：杨娟[1] 贾振红[1] 覃锡忠[1] 杨杰[2] 胡英杰 

机构地区：[1]新疆大学信息科学与工程学院,新疆乌鲁木齐830046 [2]上海交通大学图像处理与模式识别研究所,上海200240 [3]新西兰奥克兰理工大学知识工程与开发研究所

出　　处：《激光杂志》2012年第5期18-20,共3页Laser Journal

基　　金：科技部国际科技合作项目(No.2009DFA12870);教育部促进与美大地区科研合作与高层次人才培养项目

摘　　要：提出一种对Fuzzy-Shrink算法的改进图像去噪方法。该方法首先结合NSCT邻域信息和空间信息构造模糊特征,通过该模糊特征模拟NSCT变换尺度内邻域系数的相关性,再构造出模糊隶属度收缩函数对遥感图像进行去噪。仿真实验结果表明,本文提出的方法与Fuzzy-Shrink(DWT),AntShrink(DWT)去噪方法,Sure-let(DWT)去噪方法相比能够有效去除遥感图像的高斯噪声,较完整的保持图像的边缘等细节信息,提高了图像的峰值信噪比,图像视觉效果也有明显改善。A new improved Fuzzy - Shrink algorithm is proposed. In particular, intra - scale dependency within NSCT coefficients is modeled using a fuzzy feature. This feature space distinguishes between important coefficients, which belong to image discontinuity and noisy coefficients. We use this fuzzy feature for enhancing wavelet coefficients＇ information in the shrinkage step. Then a fuzzy membership function shrinks wavelet coefficients based on the fuzzy feature. The simulation experimental results show that the propesed method can effectively reduce Gauss noise in remote sensing image and preserve the image edges. Compared with the Fuzzy- Shrink {DWT）, AntShrink（DWT） method, and Sure- let （DWT） method, tile proposed method is obviously superior both in vision and in PSNR.

关 键 词：遥感图像 图像去噪 非下采样Contourlet变换(NSCT) 平移不变性 模糊隶属度函数 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]