Digital Image Processing

Abstract

Haze in the environment will hinder the accurate recognition of objects captured in an image. To overcome this problem, image dehazing processes have been an active technique applied in many research work. We introduce an effective technique to enhance the images captured and degraded due to the medium scattering and absorption. It build on the blending of two images that are directly derived from a color compensated and white-balanced version of the original degraded image. The two images to fusion, as well as their associated weight maps, are defined to promote the transfer of edges and color contrast to the output image. To avoid sharp weight map transitions that create artifacts in the low frequency components of the reconstructed image, we adapt a multiscale fusion strategy. Our dehazing technique consists in three main steps: inputs derivation from the white balanced image, weight maps definition, and multiscale fusion of the inputs and weight maps. Our Experiments are Implemented and Simulated using MATLAB.

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