结合随机匹配滤波器和特罗斯算法进行SAS图像去噪

F. Chaillan, P. Courmontagne
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引用次数: 3

摘要

SAS图像去噪的广泛研究领域表明了该问题的复杂性。用于探测水下世界的SAS设备会产生噪声损坏的数据,受到散斑噪声的强烈干扰,从而影响辐射和空间分辨率。虽然在信号处理领域存在着许多降噪滤波技术,并显示出它们的有效性,但它们都受到一个重要的限制问题:空间分辨率的下降。问题是设计一种处理方法,在保持空间分辨率的同时具有强大的去噪能力。为了完成这一任务,我们在本研究中提出了一种新的SAS图像去噪方法,该方法由一种有效的滤波技术(随机匹配滤波方法)与一种多分辨率分析技术(a tros算法)相结合而成。与一些经典方法在实际SAS数据上的比较表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Coupling the stochastic matched filter and the à Trous algorithm for SAS image de-noising
The wide research domain concerning SAS image de-noising shows the complexity of the problem. SAS devices designed to explore underwater world generate noise-corrupted data, strongly disturbed by the speckle noise, which affect both radiometric and spatial resolutions. Although many de-noising filtering techniques exist in the signal processing society and have shown their efficiency, they suffer of an important restrictive problem: the spatial resolution degradation. The matter is to design a processing having a strong de-noising power while preserving the spatial resolution. To perform this task, we present in this study a new way of SAS image de-noising consisting in coupling an efficient filtering technique, the stochastic matched filtering method, with a multi-resolution analysis technique, the a Trous algorithm. Comparison with some classical approaches on real SAS data reveal the efficiency of such an idea.
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