IEEE Trans Image Process. 2017 Sep;26(9):4389-4403. doi: 10.1109/TIP.2017.2713946. Epub 2017 Jun 8.
Speckle reduction is a longstanding topic in synthetic aperture radar (SAR) imaging. Since most current and planned SAR imaging satellites operate in polarimetric, interferometric, or tomographic modes, SAR images are multi-channel and speckle reduction techniques must jointly process all channels to recover polarimetric and interferometric information. The distinctive nature of SAR signal (complex-valued, corrupted by multiplicative fluctuations) calls for the development of specialized methods for speckle reduction. Image denoising is a very active topic in image processing with a wide variety of approaches and many denoising algorithms available, almost always designed for additive Gaussian noise suppression. This paper proposes a general scheme, called MuLoG (MUlti-channel LOgarithm with Gaussian denoising), to include such Gaussian denoisers within a multi-channel SAR speckle reduction technique. A new family of speckle reduction algorithms can thus be obtained, benefiting from the ongoing progress in Gaussian denoising, and offering several speckle reduction results often displaying method-specific artifacts that can be dismissed by comparison between results.
斑点减少是合成孔径雷达（SAR）成像中的一个长期存在的话题。由于大多数当前和计划中的 SAR 成像卫星以极化、干涉或层析模式运行，因此 SAR 图像是多通道的，必须联合处理所有通道才能恢复极化和干涉信息。SAR 信号的独特性质（复数，受乘性波动的影响）要求开发专门的方法来进行斑点减少。图像去噪是图像处理中一个非常活跃的话题，有各种各样的方法和许多可用的去噪算法，几乎总是针对加性高斯噪声抑制进行设计。本文提出了一种称为 MuLoG（带高斯去噪的多通道对数算法）的通用方案，将这种高斯去噪器包含在多通道 SAR 斑点减少技术中。因此，可以获得一系列新的斑点减少算法，受益于高斯去噪的不断发展，并提供几种斑点减少结果，通常显示出特定于方法的伪影，可以通过比较结果来消除。
