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Stick-guided lateral inhibition for enhancement of low-contrast image

The inhibitory interaction has long been observed in the lateral eye of the Limulus and been integrated into mechanism of enhancing contrast. When applying to the enhancement of low-contrast image for segmenting interested objects, the original lateral inhibition model will simultaneously amplify noises while enhancing edges contrast. This paper presents a new lateral inhibition model, which is called Stick-Guided Lateral Inhibition, for enhancement of low-contrast image so that week edges may exert a stronger force to catch the boundary of targets in the latter segmentation. First, the guided inhibition term is introduced as a general framework for improving the performance of lateral inhibition models in the presence of noises. Then, by using asymmetric sticks to guide the inhibiting process, we are able to accentuate the intensity gradients of image-edges and contours while suppressing the amplification of noises. Experiments on synthetic images and remote sensor images show that our model significantly enhances low-contrast images and improves the performance of latter segmentation.