Effective Contrast-Based Dehazing for Robust Image Matching

In this letter we present a novel strategy to enhance images degraded by the atmospheric phenomenon of haze. Our single-based image technique does not require any geometrical information or user interaction enhancing such images by restoring the contrast of the degraded images. The degradation of the finest details and gradients is constrained to a minimum level. Using a simple formulation that is derived from the lightness predictor our contrast enhancement technique restores lost discontinuities only in regions that insufficiently represent original chromatic contrast of the scene. The parameters of our simple formulation are optimized to preserve the original color spatial distribution and the local contrast. We demonstrate that our dehazing technique is suitable for the challenging problem of image matching based on local feature points. Moreover, we are the first that present an image matching evaluation performed for hazy images. Extensive experiments demonstrates the utility of the novel technique.