Recent improvements on perceptual processing using DAF wavelets
Zhenghao Shi, D. Zhang, Huiying Wang, Donald Jack Kouri, David K. Hoffman · 2002
New wavelet techniques are designed to improve the perceptual quality of images/signal, enhance and detect the detail features in the region of interest (ROI). Distributed approximating functionals (DAFs) are used to construct a new class of smooth wavelets, which enable better signal processing performance. This paper is focused on improvements in DAF wavelet signal processing. The combined perceptual techniques (such as regularization, visual group normalization and contrast nonlinear enhancement) produce natural high-quality images based on the human vision system. The underlying technologies significantly facilitate the creation of generic signal processing and computer-aided diagnostic (CAD) systems.