Abstract

A novel method for filtering images contaminated by mixed (additive-multiplicative) noise is substantiated and implemented for the first time. The method includes several stages: the formation of similar structures in 3D space, homomorphic transformation, a 3D filtering approach based on a sparse representation in the discrete cosine transform space, inverse homomorphic transformation, and final post-processing that involves bilateral filtering and the reconstruction of edges and details. A physical interpretation of the filtering procedure under mixed noise conditions is given, and a filtering block diagram is developed. Numerous experiments based on the developed method have confirmed its superiority in term of conventional criteria, such as the structural similarity index measure and the peak signal-to-noise ratio, as well as in term of visual image quality via human perception.

中文翻译：

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加减乘积噪声破坏的图像的3D滤波

摘要

首次证实并实现了一种新颖的过滤方法，该方法用于过滤被混合（加乘）噪声污染的图像。该方法包括几个阶段：在3D空间中形成相似的结构，同态变换，基于离散余弦变换空间中的稀疏表示的3D滤波方法，逆同态变换以及涉及双边滤波和重构的最终后处理边缘和细节。给出了混合噪声条件下滤波过程的物理解释，并给出了滤波框图。根据开发的方法进行的大量实验已经证实了其在常规标准方面的优越性，例如结构相似性指标测量和峰值信噪比，