Abstract

Discrete orthogonal transforms (DOTs) are important in many applications, including image and signal processing. Novel 1D and 2D bit-level systolic architectures are presented for the efficient implementation of DOTs for image and signal processing. The authors describe the design methodology of the techniques based on the Baugh-Wooley algorithm, and the associated design including a case study of an FPGA implementation. They also discuss the efficiency of implementations which have O(N-2) and O(2nN) as the area and time complexities for 2D structures, respectively, and O(N) and O(2nN) as the area and time complexities for 1D structures, respectively (where N is the transform length and n is the word length). Furthermore, it is shown that the architectures are parameterisable and that the area required by the designs can be predicted for different values of N and n. A comparison with existing and similar structures has shown that the proposed architectures perform better.