Chromatic Improvement of Backgrounds Images Captured with Environmental Pollution Using Retinex Model

Abstract

A commonly problem of digital image processing systems that use video cameras for control navigation, as those used in cars or planes control, is that these systems depend on image contrast and the environmental pollution as fog, smog or rain. These environment characteristics, filters wavelengths of the light, which causes that the captured images, were modified by the video camera, decreasing its efficiency. It is proposed to improve the chromatic content of captured images, where environmental pollution is present, using the Retinex model. This algorithm implementation uses different characteristics such as lightness changes and color contrast; these characteristics produce different results for every Retinex model proposed showing differences in color and luminance modification of the captured image. In this paper are proposed and compared three different Retinex models; these models are the Simple Retinex, the Multi-scale Retinex and the Multi-scale Retinex with Color Correction.