An Efficient Design Approach of ROI Based DWT Using Vedic and Wallace Tree Multiplier on FPGA Platform

Abstract

In digital image processing, the compression mechanism is utilized to enhance the visual perception and storage cost. By using hardware architectures, reconstruction of medical images especially Region of interest (ROI) part using Lossy image compression is a challenging task. In this paper, the ROI Based Discrete wavelet transformation (DWT) using separate Wallace- tree multiplier (WM) and modified Vedic Multiplier (VM) methods are designed. The Lifting based DWT method is used for the ROI compression and reconstruction. The 9/7 filter coefficients are multiplied in DWT using Wallace- tree multiplier (WM) and modified Vedic Multiplier (VM). The designed Wallace tree multiplier works with the parallel mechanism using pipeline architecture results with optimized hardware resources, and 8x8 Vedic multiplier designs improves the ROI reconstruction image quality and fast computation. To evaluate the performance metrics between ROI Based DWT-WM and DWT-VM on FPGA platform, The PSNR and MSE are calculated for different Brain MRI images, and also hardware constraints include Area, Delay, maximum operating frequency and power results are tabulated. The proposed model is designed using Xilinx platform using Verilog-HDL and simulated using ModelSim and Implemented on Artix-7 FPGA device.