AN ARTIFACT-FREE WAVELET MODEL FOR PERCEPTUAL CONTRAST ENHANCEMENT OF COLOR IMAGES

摘要

Contrast enhancement of color images can prove to be a difficult task because artifacts and unnatural colors can appear after the process. In this paper we propose a wavelet-based variational framework in which contrast enhancement is obtained through the minimization of a suitable energy functional of wavelet coefficients. We will show that this new approach has certain advantages with respect to the usual spatial techniques sustained by the fact that the wavelet representation is intrinsically local, multiscale and sparse. The Euler-Lagrange equations of the model are implicit equations involving the detail wavelet coefficients of the image. These equations can be quickly solved by Newton's method, so that the algorithm can rapidly compute the enhanced detail coefficients. We will discuss the influence of the parameters tests on natural images to show that the method is artifact free within an ample range of variability of its parameters.