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

Digital Signal Processing(2013)

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摘要
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.
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关键词
automatic contrast enhancement,conventional method,image sequence,non-linear enhancement function,wavelet coefficient,shrinkage function,proposed enhancement method,local statistic,low-light image,noise amplification,simultaneous noise reduction,new method,noise reduction,contrast enhancement,denoising,helium,dispersion,wavelet transforms,noise,statistical analysis,pixel,wavelets,statistical modelling
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