Single Image Super-Resolution via the Implementation of the Hardware-Friendly Sparse Coding

Zhekang Dong, Chun Sing Lai, Zhao Xu, Donglian Qi

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

4 Citations (Scopus)

Abstract

Sparse representation is one of the effective approaches to perform the feature extraction on the high-dimensional signals and has been widely used in the field of image processing. In this paper, a novel single image super-resolution (SR) reconstruction algorithm based on sparse coding is presented. Specifically, due to the fact that sparse coding has the potential to greatly facilitate the biological-neural system and to deal with a large amount of complex data, while consuming a finite amount of energy, a memristor crossbar array synthesized by a threshold-type memristor model is constructed for the implementation of a hardware-friendly sparse coding method, i.e., the Locally Competitive Algorithm (LCA). Meanwhile, the relevant online dictionary learning method is provided, along with the description of weight programming strategy. Furthermore, the specific description of the image SR via the LCA sparse coding is provided. For the verification purpose, a series of experiments are carried out to illustrate the validity and effectiveness of the entire scheme.

Original languageEnglish
Title of host publicationProceedings of the 37th Chinese Control Conference, CCC 2018
EditorsXin Chen, Qianchuan Zhao
PublisherIEEE Computer Society
Pages8132-8137
Number of pages6
ISBN (Electronic)9789881563941
DOIs
Publication statusPublished - 5 Oct 2018
Event37th Chinese Control Conference, CCC 2018 - Wuhan, China
Duration: 25 Jul 201827 Jul 2018

Publication series

NameChinese Control Conference, CCC
Volume2018-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference37th Chinese Control Conference, CCC 2018
Country/TerritoryChina
CityWuhan
Period25/07/1827/07/18

Keywords

  • Dictionary learning
  • Image super-resolution
  • Memristor crossbar array
  • Sparse coding

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Applied Mathematics
  • Modelling and Simulation

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