Noise Aware L₂-LP Decomposition-Based Enhancement in Extremely Low Light Conditions With Web Application
Neha Singh, Ashish Kumar Bhandari
Abstract
In this article, an algorithm is introduced which not only focuses on enhancing low light images but also denoises images to produce more visually pleasing outputs. It is observed that various methods ignore noise during enhancement processes. This causes, enhancement of noise which leads to significant information lost. The paper projected a novel framework for low light images that performs enhancement and denoising jointly. The proposed paper uses <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$L_{2}$ </tex-math></inline-formula> - <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$L_{P}$ </tex-math></inline-formula> image decomposition to obtain reflectance and illumination concurrently. The illumination layer is corrected using the proposed weighting distribution and generates enhanced output. Further to this, noise suppressed bilateral filter is employed here for denoising process and gamma function is applied in subsequent step for additional contrast improvement. Experimental trials illustrate that the proposed method yields result with good contrast and brightness when it is compared to various enhancement techniques.