Implementation of Modified Lifting and Flipping Plans in D.W.T Architecture for Better Performance

Data compression is one of the major fields of research in the present world. In this regard image compression is also having its own significance, so many algorithms for DFT, DCT, DWT, etc. have been developed and among them DWT is most likely used there are two plans are existing for generating 2-DWT and are lifting and flipping plans. The above two plans architecture are having its own fixed scaling constants, multipliers and adders. In my project work I am proposing a lifting plan and flipping plan such that the modification is done in its internal architecture of S.M.B.Multiplier and radix-4 booth multiplier with replacing adder in it with spanning tree parallel prefix adder. This modification has improved Power Delay Product (PDP) by 7% in lifting plan and 5% in flipping plan

Discrete Wavelet Transforms

The discrete wavelet transform (DWT) algorithms have a firm position in processing of signals in several areas of research and industry. As DWT provides both octave-scale frequency and spatial timing of the analyzed signal, it is constantly used to solve and treat more and more advanced problems. The present book: Discrete Wavelet Transforms: Algorithms and Applications reviews the recent progress in discrete wavelet transform algorithms and applications. The book covers a wide range of methods (e.g. lifting, shift invariance, multi-scale analysis) for constructing DWTs. The book chapters are organized into four major parts. Part I describes the progress in hardware implementations of the DWT algorithms. Applications include multitone modulation for ADSL and equalization techniques, a scalable architecture for FPGA-implementation, lifting based algorithm for VLSI implementation, comparison between DWT and FFT based OFDM and modified SPIHT codec. Part II addresses image processing algorithms such as multiresolution approach for edge detection, low bit rate image compression, low complexity implementation of CQF wavelets and compression of multi-component images. Part III focuses watermaking DWT algorithms. Finally, Part IV describes shift invariant DWTs, DC lossless property, DWT based analysis and estimation of colored noise and an application of the wavelet Galerkin method. The chapters of the present book consist of both tutorial and highly advanced material. Therefore, the book is intended to be a reference text for graduate students and researchers to obtain state-of-the-art knowledge on specific applications