<title>WaveNet compressed-image restoration brassboard design</title>

Abstract

Recent advances in areas such as wavelet mathematics, and artificial neural networks have resulted in improved image compression, restoration, and filtering techniques. Although these techniques are capable of achieving excellent performance in terms of image quality, their computational complexity often requires expensive, and specialized hardware to run in near real time. Even general purpose parallel processing boards exceed the cost, size, and weight constraints of many applications including, remote sensors, security systems, commercial and home video teleconferencing. This paper describes a low cost board which supports a video compression, restoration, and filter system. The WaveNet board has been optimized for wavelet based compression techniques, and neural network based filters.