The 2d Discrete Wavelet Transform on Programmable Graphics Hardware

The growing popularity of the Discrete Wavelet Transform (DWT) has boosted its tuning on all sorts of computer systems, from special purpose hardware for embedded systems to general purpose microprocessors and multiprocessors. In this paper we continue to investigate possibilities for the implementation of the DWT, focusing on state-of-the-art programmable graphics hardware. Current design trends have transformed these devices into powerful coprocessors with enough flexibility to perform intensive and complex floating-point calculations. This study is concentrated on the comparison between the most popular implementation alternatives, known as the lifting and filterbank algorithms. The characteristics of the filter-bank version suggest a better mapping on current graphics hardware, given that they present a higher degree of parallelism. However, our experiments show that the lifting algorithm, which exhibits lower computational demands, can be efficiently tailored to provide best results despite the data dependencies involved in this scheme, which makes the exploitation of data parallelism more difficult.