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

Abubakar Abubakar, Xiaojin Zhao, Shiting Li, Maen Takruri, Eesa Bastaki, Amine Bermak

Research output: Contribution to journalArticle

7 Citations (Scopus)


In this paper, we present a Block-Matching and 3D 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 2D image patches to form a 3D 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 (PCA) in terms of peak-signal-to-noise-ratio (PSNR) and Structural Similarity (SSIM) 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.

Original languageEnglish
JournalIEEE Sensors Journal
Publication statusAccepted/In press - 27 Jul 2018



  • 3D block grouping
  • collaborative filtering
  • division of focal plane
  • Filtering
  • image denoising
  • Image sensors
  • Interpolation
  • Polarization image
  • Sensors
  • Three-dimensional displays
  • Wiener filters

ASJC Scopus subject areas

  • Instrumentation
  • Electrical and Electronic Engineering

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