An automatic contrast enhancement method based on stochastic resonance

Visual quality enhancement plays a vital role in low cost imaging systems, machine vision, industrial applications, remote sensing, face recognition systems and medical image interpretation etc. Growth of low cost image processing applications require image preprocessing which enhances details of an image. Most of the contrast enhancement papers apply desired contrast enhancement technique directly to enhance the given input image having poor contrast or contrast at any other undesired level. It is important to predict whether the contrast enhancement is needed for an image, to avoid the artifacts due to enhancement on the good image. In this paper, an algorithm to model images using its local contrast measure has been proposed, to classify and distinguish between the images having different contrast level. The input image is classified either as low contrast or high contrast image using the model. If the classified image is low contrast it will be enhanced using the Stochastic Resonance principle. The results show that the proposed automated procedure enhances the low contrast image better than the conventional enhancement methods.