Biologically Inspired Contrast Enhancement Using Asymmetric Gain Control

Abstract

A neuro-physiologically inspired model is presented for the contrast enhancement of images. The contrast of an image is calculated using simulated on- and off-centre receptive fields whereby obtaining the corresponding two contrast maps. We propose an adaptive asymmetric gain control function that is applied to the two contrast maps which are then used to reconstruct the image resulting in its contrast enhancement. The image's mean luminance can be adjusted as desired by adjusting the asymmetricity between the gain control factors of the two maps. The model performs local contrast enhancement in the contrast domain of an image where it lends itself very naturally to such adjustments. Furthermore, the model is extended on to colour images using the concept of colour-opponent receptive fields found in the human visual system. The colour model enhances the contrast right in the colour space without extracting the luminance information from it. Being neuro-physiologically plausible, this model can be beneficial in theorising and understanding the gain control mechanisms in the primate visual system. We compare our results with the CLAHE algorithm.