FPGA implementation of fully parallel distributed arithmetic based DCT architecture

Abstract

The paper describes the design of 2D-discrete cosine transform (DCT) which is widely used in image and video compression algorithms. The objective of this paper is to design a fully parallel distributed arithmetic (DA) architecture for 2Ddimensional DCT to be implemented on field programmable gate array (FPGA). DCT requires large amount of mathematical computations including multiplications and accumulations. The multipliers consume increased power and area; hence multipliers are completely discarded in the proposed design. Distributed arithmetic is a method of modification at bit stream for sum of product or vector dot product to hide the multiplications. DA is very much suitable for FPGA designs as it reduces the size of a multiply and accumulate hardware. The speed is increased in the proposed design with the fully parallel approach. In this work, existing DA architecture for 2D-DCT and the proposed area efficient fully parallel DA architecture for 2D-DCT are realized. The simulation and synthesis is performed using Xilinx ISE.Index Terms-2DDiscrete cosine transform, Parallel Architecture, Distributed Arithmetic, and FPGA.

Algorithm development and hardware implementation for medical image compression system: a review

“…The capability to develop a programmable circuit architecture with the flexibility of computational, memory, speed and power requirement, FPGAs seem an ideal candidate to be proposed as a hardware technology for prototype a simple, moderate and complex applications [2], [10]. Indeed, other advantages offered by FPGAs are massive parallelism capabilities, multimillion gate counts and special low-power packages [6,11].…”

“…Despite its complexity, there has been an interest in three-dimensional (3-D) curvelet transform implementation on various platforms. Previous surveys have classified this research field into two categories: algorithms development [14][15][16] and algorithms with hardware implementation [11,12]. Moreover, a huge gap stills remain for further research in exploiting reconfigurable computing for 3-D medical image compression in the form of two major limitations: a) Discrete curvelet transform algorithm has not been widely explored in designing 3-D medical image compression system.…”