Hybrid Kronecker compressive sensing for images

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Natural images has certain level of both similarity and difference which can be efficiently represented by deterministic and random sensing matrices in compressive sensing. In this context, a hybrid sensing matrix which combines a deterministic DCT and a random matrix, is recently investigated. In this paper, we bring the concept of hybrid sensing matrix into Kronecker compressive sensing (KCS) of images. Extensive experiment has shown that the proposed hybrid KCS method performs better than either fully random or deterministic DCT matrix, and comparatively with other state-of the-art sensing schemes in terms of reconstruction quality.

Original languageEnglish
Title of host publication2014 International Conference on Advanced Technologies for Communications, ATC 2014
PublisherIEEE Computer Society
Pages554-558
Number of pages5
ISBN (Electronic)9781479969555
DOIs
StatePublished - 17 Feb 2015
Event2014 7th International Conference on Advanced Technologies for Communications, ATC 2014 - Hanoi, Viet Nam
Duration: 15 Oct 201417 Oct 2014

Publication series

NameInternational Conference on Advanced Technologies for Communications
Volume2015-February
ISSN (Print)2162-1039
ISSN (Electronic)2162-1020

Conference

Conference2014 7th International Conference on Advanced Technologies for Communications, ATC 2014
Country/TerritoryViet Nam
CityHanoi
Period15/10/1417/10/14

Keywords

  • DCT kernel
  • hybrid sensing matrix
  • Kronecker compressive sensing
  • total variation

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