Biologically Inspired Contrast Enhancement Using Asymmetric Gain Control

A neuro-physiologically inspired model is presented for the contrast enhancement of images. The contrast of an im-age is calculated using simulated on- and off-centre recep-tive fields whereby obtaining the corresponding two con-trast maps. We propose an adaptive asymmetric gain con-trol function that is applied to the two contrast maps which are then used to reconstruct the image resulting in its con-trast 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 per-forms local contrast enhancement in the contrast domain of an image where it lends itself very naturally to such adjust-ments. Furthermore, the model is extended on to colour im-ages using the concept of colour-opponent receptive fields found in the human visual system. The colour model en-hances the contrast right in the colour space without ex-tracting 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.