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

Authors:
Artur Łoza;David R. Bull;Paul R. Hill;Alin M. Achim
Affiliations:
Department of Electrical and Computer Engineering, Khalifa University of Science, Technology and Research, United Arab Emirates;Department of Electrical and Electronic Engineering, University of Bristol, UK;Department of Electrical and Electronic Engineering, University of Bristol, UK;Department of Electrical and Electronic Engineering, University of Bristol, UK
Venue:
Digital Signal Processing
Year:
2013

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Abstract

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.