Enhancement of noisy low-light images via structure-texture-noise decomposition

  • Jaemoon Lim
  • , Minhyeok Heo
  • , Chul Lee
  • , Chang Su Kim

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

3 Scopus citations

Abstract

We propose a novel noisy low-light image enhancement algorithm via structure-texture-noise (STN) decomposition. We split an input image into structure, texture, and noise components, and enhance the structure and texture components separately. Specifically, we first enhance the contrast of the structure image, by extending a 2D histogram-based image enhancement scheme based on the characteristics of low-light images. Then, we reconstruct the texture image by retrieving texture components from the noise image, and enhance it by exploiting the perceptual response of the human visual system. Experimental results demonstrate that the proposed STN algorithm sharpens the texture and enhances the contrast more effectively than conventional algorithms, while removing noise without artifacts.

Original languageEnglish
Title of host publication2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9789881476821
DOIs
StatePublished - 17 Jan 2017
Event2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016 - Jeju, Korea, Republic of
Duration: 13 Dec 201616 Dec 2016

Publication series

Name2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016

Conference

Conference2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016
Country/TerritoryKorea, Republic of
CityJeju
Period13/12/1616/12/16

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