Literature DB >> 30827710

A new MNF-BM4D denoising algorithm based on guided filtering for hyperspectral images.

Ping Xu1, Bingqiang Chen1, Lingyun Xue2, Jingcheng Zhang3, Lei Zhu1, Hangbo Duan1.   

Abstract

This paper proposed a new MNF-BM4D denoising algorithm based on guided filtering to improve the denoising performance of the state-of-the-art Block-Matching and 4D filtering(BM4D) algorithm for hyperspectral images in the spatial and spectral domain. BM4D is firstly used to denoise hyperspectral images. Then Minimum Noise Fraction(MNF) algorithm is introduced to distinguish between the main component and the noisy component. Finally, the guided image filtering technology is utilized to further improve the denoising performance. A number of experiments on both simulated and real data are conducted to validate the effective denoising performance of the proposed method. Therefore, the proposed algorithm can be considered as a promising technique for hyperspectral imagery denoising.
Copyright © 2019 ISA. Published by Elsevier Ltd. All rights reserved.

Keywords:  BM4D; Denoising; Guided filtering; Hyperspectral images; MNF

Year:  2019        PMID: 30827710     DOI: 10.1016/j.isatra.2019.02.018

Source DB:  PubMed          Journal:  ISA Trans        ISSN: 0019-0578            Impact factor:   5.468


  2 in total

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Journal:  Sensors (Basel)       Date:  2020-01-07       Impact factor: 3.576

2.  Non-Local SVD Denoising of MRI Based on Sparse Representations.

Authors:  Nallig Leal; Eduardo Zurek; Esmeide Leal
Journal:  Sensors (Basel)       Date:  2020-03-10       Impact factor: 3.576

  2 in total

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