Synthesis and selection of DCT algorithms using behavioral synthesis-based algorithm space exploration

Abstract

Numerous fast algorithms for the discrete cosine transform (DCT) have been proposed in image and video processing literature. Until recently, it has been difficult to compare different DCT algorithms and select one which is best suited for implementation under a given set of design goals and constraints. In this paper, we propose an approach for design space exploration at the algorithm and behavioral levels using high level synthesis tools. In particular, we study and compare the following nine DCT algorithms: Lee's, Wang's, DIT, DFT, QR, Givens, Arai, MCM, and direct algorithm. The main conclusion of this study is that the best choice among fast DCT algorithms depends on a particular set of design goals and constraints. Another important conclusion is that for almost all sets of implementation goals and constraints more than an order of magnitude improvement can be achieved using algorithm and behavioral design space exploration.