Automatic contrast enhancement of low-light images based on local statistics of wavelet coefficients

Artur Loza*, David R. Bull, Paul R. Hill, Alin M. Achim

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

131 Citations (Scopus)


This paper describes a new method for contrast enhancement in images and image sequences of low-light or unevenly illuminated scenes based on statistical modelling of wavelet coefficients of the image. A non-linear enhancement function has been designed based on the local dispersion of the wavelet coefficients modelled as a bivariate Cauchy distribution. Within the same statistical framework, a simultaneous noise reduction in the image is performed by means of a shrinkage function, thus preventing noise amplification. The proposed enhancement method has been shown to perform very well with insufficiently illuminated and noisy imagery, outperforming other conventional methods, in terms of contrast enhancement and noise reduction in the output data. (c) 2013 Elsevier Inc. All rights reserved.

Original languageEnglish
Pages (from-to)1856-1866
Number of pages11
JournalDigital Signal Processing: a Review Journal
Issue number6
Publication statusPublished - Dec 2013


  • Wavelets
  • Statistical modelling
  • Image and video contrast enhancement
  • Denoising


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