Pre-selection based non-local passive millimeter wave image denoising algorithm

Wang Yang Yu, Xiang Guang Chen*, Lei Wu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Given that the low resolution and poor texture information of passive millimeter wave images, a pre-selection based image de-noising algorithm (PBNL) was proposed in this paper. The local regional characteristics of the image were obtained by using the singular value decomposition (SVD) of image gradient information, then the image was divided into different categories, and relevant algorithms were adopted. Experimental results show that, in contrast to the non local means (NL-Means) algorithm, the computational time complexity of the method proposed in this paper is significantly reduced and peak signal-to-noise ratio (PSNR) is superior to current state-of-art denoising algorithms, such as BM3D, anisotropic denoising algorithm, and it can get a better recognition results visually.

Original languageEnglish
Pages (from-to)1303-1307
Number of pages5
JournalBeijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume35
Issue number12
DOIs
Publication statusPublished - 1 Dec 2015

Keywords

  • Non-local means
  • Passive millimeter wave
  • Pre-selection
  • Singular value decomposition

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