Back to articles
Articles
Volume: 32 | Article ID: art00018
Image
Hyperspectral complex-domain image denoising: cube complex-domain BM3D (CCDBM3D) algorithm
  DOI :  10.2352/ISSN.2470-1173.2020.10.IPAS-179  Published OnlineJanuary 2020
Abstract

We consider hyperspectral phase/amplitude imaging from hyperspectral complex-valued noisy observations. Block-matching and grouping of similar patches are main instruments of the proposed algorithms. The search neighborhood for similar patches spans both the spectral and 2D spatial dimensions. SVD analysis of 3D grouped patches is used for design of adaptive nonlocal bases. Simulation experiments demonstrate high efficiency of developed state-of-the-art algorithms.

Subject Areas :
Views 101
Downloads 2
 articleview.views 101
 articleview.downloads 2
  Cite this article 

Vladimir Katkovnik, Mykola Ponomarenko, Karen Egiazarian, Igor Shevkunov, Peter Kocsis, "Hyperspectral complex-domain image denoising: cube complex-domain BM3D (CCDBM3D) algorithmin Proc. IS&T Int’l. Symp. on Electronic Imaging: Image Processing: Algorithms and Systems XVIII,  2020,  pp 179-1 - 179-7,  https://doi.org/10.2352/ISSN.2470-1173.2020.10.IPAS-179

 Copy citation
  Copyright statement 
Copyright © Society for Imaging Science and Technology 2020
72010604
Electronic Imaging
2470-1173
Society for Imaging Science and Technology
7003 Kilworth Lane, Springfield, VA 22151 USA