Limited by the number of available photons collected by a pixel and the stability of the
imaging system, images captured under poor illumination conditions are often degraded by …

Low-light image enhancement methods based on classic Retinex model attempt to
manipulate the estimated illumination and to project it back to the corresponding reflectance …

This paper presents an optimization-based low-light image enhancement method using
spatially adaptive l 2-norm based Retinex model. The proposed method adaptively enforces …

Guided by the Retinex model, image decomposition based low-light image enhancement
methods attempt to manipulate the estimated illumination and project it back to the …

For low-light image enhancement, Retinex-based models have been acknowledged as a
representative technique, yet they frequently amplify noise hidden in dark image. There …

This paper presents a dual autoencoder network model based on the retinex theory to
perform the low-light enhancement and noise reduction by combining the stacked and …

Noise causes unpleasant visual effects in low-light image/video enhancement. In this paper,
we aim to make the enhancement model and method aware of noise in the whole process …

Low-light image enhancement is an important task in the domain of computer vision. Images
taken under insufficient lighting conditions manifest low visibility and unknown noises which …

Low-light image enhancement aims to improve the quality of images captured under low-
lightening conditions, which is a fundamental problem in computer vision and multimedia …

Image enhancement is a fundamental low-level task of significant importance that can
directly affect high-level image processing tasks. Although various methods have been …