High performance 2D parallel block-filtering system for real-time imaging applications using the Sharc ADSP21060

Abstract

A simple and efficient design and implementation of the two-dimensional (2D) parallel block-filtering algorithm by fast number theoretic transforms is presented. The algorithm is generalized to accommodate any filter size for optimum segmentation of the input data in order to achieve efficient filtering and optimal parallelization. The 2D algorithm is found to improve the performance of digital filtering systems by segmenting the 2D input into smaller block sizes, which are shown to be efficient and lead to highly parallel implementation. In this paper the parallel architecture of the 2D block-filtering method is presented and the implementation of fast 2D block filtering using the 2D new Mersenne number transform (2D NMNT) for digital filtering is demonstrated on a multi-processor platform. The mathematical derivations of the input stage, output stage and the direct 2D FIR filtering equation are also given. The algorithm's efficiency is tested, and new results are given showing an improved performance, as evidenced by the highly parallel algorithm structure and the use of smaller transform sizes.