Abstract
It is known that an image enhancement model is based on the Human Visual System Image enhancement processing normally decreases image quality in some aspects, because the representation of color space is not linear. Generally The Retinex algorithm can be used in many kinds of images by considering human visual perception. The existing Retinex algorithm, both Single-Scale Retinex and Multiple-Scale Retinex, do not take the local variations of the contrast into account within an image science. Therefore, the performance of these models is limited. A modified Retinex algorithm using non-isotropic Gaussian kernel filters to fit the human visual system and the image perception quality is increased by equalizing the obtained Retinex ratio in logarithm. The process is accomplished by coping with the various scales of the window-supporting regions yielding multi-scale enhanced images. Many experiments are conducted to demonstrate the performance of the proposed algorithm.
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