Hybrid perceptual image processing using new interpolating wavelets

Abstract

New wavelet techniques are employed to improve the perceptual quality of images, and to enhance and detect the detail features in the region of interest (ROI). Distributed approximating functionals (DAFs) are used to construct a new class of interpolating wavelets, which enable better image processing performance. This paper is focused on recent improvements in DAF wavelet image processing. The combined perceptual techniques (such as visual group normalization and contrast nonlinear enhancement) produce natural high-quality images adapted to the human vision system. The underlying technologies significantly facilitate the creation of generic image processing and computer-aided diagnostic (CAD) systems.