A Novel Design of Symmetric Daub-4 Wavelet Filter Bank for Image Analysis

Abstract

The orthogonal wavelet filter banks (FBs) consume large resources for hardware implementation due to their irrational coefficients. This results in reduction in speed of operation, huge memory requirement and increased power dissipation. In order to solve these issues, a low complex symmetric Daub-4 (8-tap) orthogonal wavelet FB is proposed in this brief. This is achieved by slightly altering the perfect reconstruction (PR) condition to make proposed FB symmetric and to obtain dyadic filter coefficients. The proposed wavelet FB is multiplier free and achieves considerably reduction in hardware and dynamic power consumption by reducing number of adders and shifters. This is verified by implementing the proposed wavelet FB on Kintex-7 field programmable gate array (FPGA) using vivado 2019.2 software from Xilinx. The proposed FB is tested for its suitability in applications such as image compression and medical image retrieval. Simulations results prove that the designed wavelet FB gives better performances in terms of PSNR for image compression and retrieval accuracy (ARP, ARR) for medical image retrieval on the benchmark images as compared to state-of-art methods.