A New Approach to the Design and Implementation of a Family of Multiplier Free Orthogonal Wavelet Filter Banks

Abstract

This paper presents a generalized novel design of a family of multiplier free orthogonal wavelet filter banks (FBs) with low complexity. In the proposed method, maximum number of zeros at <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$z=-1$ </tex-math></inline-formula> is ensured for a desired length of analysis and synthesis filters. A new class of technique is proposed to obtain dyadic filter coefficients based on double shifting orthogonality property with allowable deviation from original filter coefficients. This is achieved by slightly altering perfect reconstruction (PR) condition to obtain dyadic filter coefficient. A general closed form expression is formulated using double shifting orthogonality property to reduce the error between original filter coefficients and proposed dyadic filter coefficients. The designed wavelet FB improved time-frequency product, Sobolev regularity and frequency selectivity (low energy in error) over well known existing wavelet FBs. In addition, a fixed point VLSI architecture is proposed for the designed family of orthogonal wavelet FBs. The suggested architecture is designed and implemented on Kintex7 FPGA board. The proposed family of orthogonal wavelet FBs is multiplier less with significantly reduced adders, shifters and dynamic power dissipation. The performance of the proposed wavelet FB is validated on two different applications namely image compression and medical image retrieval. The proposed FBs are tested on well known datasets such as CLASSIC, EPFL, RAISE, and FiveK for image compression and on three different medical image databases such as NEMA, OASIS, and EXACT09 for image retrieval.