A novel framework for low-light colour image enhancement and denoising

Abstract

This article describes a novel framework for low-light colour image enhancement and denoising. To avoid influences from different colour channels, noise reduction and brightness/contrast enhancement are performed in different colour spaces. In the HSI space, the Bilateral filter is used for illumination- and reflection-component separation, and is effective for edge-preservation, halo removal and noise suppression. Brightness/contrast are extrapolated by using a newly designed histogram, where a suppression term based on the statistics of mathematical expectation and standard deviation was added to improve the algorithm's adaptability. Meanwhile, a saturation enhancement function was proposed to ensure more natural colours. In the YCbCr space, based on noise characteristics in low-light images, Gaussian and Median filters were adopted to reduce the noise. Experimental results indicate that the algorithm is effective for low illumination compensation, colour restoration and noise reduction.