Speckle noise reduction in SAS imagery
Speckle noise reduction in SAS imagery
复制标题
DOI：
10.1016/j.sigpro.2006.08.001
复制
发表时间：
2007-04-01
影响因子：
4.4
通讯作者：
Courmontagne, Philippe
中科院分区：
文献类型：
--
作者：
Chaillan, Fabien;Fraschini, Christophe;Courmontagne, Philippe
合成孔径声纳（SAS）被积极用于海底成像。事实上，SAS提供的高分辨率图像是非常感兴趣的，特别是对于躺在海床上的物体的检测、定位和最终分类。SAS图像被称为散斑噪声的粒状乘性噪声严重破坏，这降低了空间和辐射分辨率。本文的目的是提出一种新的自适应处理，允许图像滤波，为加性和乘性噪声的情况下。这个新的过程是基于多分辨率变换和滤波方法之间的婚姻。这里使用的滤波技术是基于二维随机匹配滤波方法，它最大化处理后的信噪比，最小化信号的近似值和原始信号之间的均方误差。对真实的SAS数据得到的结果，并与使用经典处理得到的结果进行了比较。(c)2006 Elsevier B.V.保留所有权利。
Synthetic aperture sonar (SAS) is actively used in sea bed imagery. Indeed high resolution images provided by SAS are of great interest, especially for the detection, localization and eventually classification of objects lying on sea bed. SAS images are highly corrupted by a granular multiplicative noise, called speckle noise which reduces spatial and radiometric resolutions. The purpose of this article is to present a new adaptive processing that allows image filtering, for both the additive and multiplicative noise case. This new process is based on the marriage between a multi-resolution transformation and a filtering method. The filtering technique used here is based on the two-dimensional stochastic matched filtering method, which maximizes the signal-to-noise ratio after processing and minimizes mean square error between the signal's approximation and the original one. Results obtained on real SAS data are presented and compared with those obtained using classical processing. (c) 2006 Elsevier B.V. All rights reserved.