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Improved iterative contourlet algorithm for astronomical image denoising

  • Harbin Institute of Technology

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

Abstract

Research on compressed sensing (CS) reconstruction algorithm. To solve the problem of lower convergence speed in compressed sensing iterative algorihtm (ICWF) based on contourlet wiener filtering, a Dai-Yuan linear search step size is used to adjust the convergence speed in this paper, and then an improved ICWF algorithm is proposed. At the same time, the proposed algorithm is applied for astronomical image denoising. Number experimental results demonstrate that the proposed algorithm is superior to the traditional ICWF algorithm in terms of convergence speed and visual quality, meanwhile which can effectively protect the astronomical image detail information.

Original languageEnglish
Title of host publicationProceedings of the 29th Chinese Control and Decision Conference, CCDC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4833-4837
Number of pages5
ISBN (Electronic)9781509046560
DOIs
StatePublished - 12 Jul 2017
Event29th Chinese Control and Decision Conference, CCDC 2017 - Chongqing, China
Duration: 28 May 201730 May 2017

Publication series

NameProceedings of the 29th Chinese Control and Decision Conference, CCDC 2017

Conference

Conference29th Chinese Control and Decision Conference, CCDC 2017
Country/TerritoryChina
CityChongqing
Period28/05/1730/05/17

Keywords

  • Astronomical Image
  • Compressed Sensing
  • Contourlet
  • Wiener Filtering

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