A Block-Matching and 3-D Filtering Algorithm for Gaussian Noise in DoFP Polarization Images

In this paper, we present a block-matching and 3-D filtering (BM3D) algorithm dedicated to the division-of-focal-plane (DoFP) polarization images. This algorithm based on a non-local collaborative filtering method is capable of exploiting all the different polarization channels simultaneously. Compared with the previously reported implementations for DoFP sensors, the proposed algorithm attenuates Gaussian noise in the transform domain by stacking similar 2-D image patches to form a 3-D block. According to our extensive experimental results, the proposed algorithm outperforms all the existing denoising algorithms for DoFP images including the state-of-the-art principle component analysis in terms of peak-signal-to-noise-ratio and structural similarity index. Moreover, the comparison is further extended to visual comparison, it is indicated that the image details are well-preserved by the proposed BM3D algorithm.