Design and Implementation of an RNS-based 2D DWT Processor

No abstract availabl

Complexity Reduction and Fast Algorithm for 2-D Integer Discrete Wavelet Transform Using Symmetric Mask-Based Scheme

[[abstract]]Wavelet coding has been shown to be better than discrete cosine transform (DCT) in image/video processing. Moreover, it has the feature of scalability, which is involved in modern video standards. This work presents novel algorithms, namely 2-D symmetric mask-based discrete wavelet transform (SMDWT), to improve the critical issue of the 2-D lifting-based discrete wavelet transform (LDWT), and then obtains the benefit of low latency, high-speed operation, and low temporal memory. The SMDWT also has the advantages of high-performance embedded periodic extension boundary treatment, reduced complexity, regular signal coding, short critical path, reduced latency time, and independent subband coding processing. Moreover, the 2-D lifting-based DWT performance can also be easily improved by exploiting appropriate parallel method inherently in SMDWT. Comparing with the normal 2-D 5/3 integer lifting-based DWT the proposed method significantly improves lifting-based latency and complexity in 2-D DWT without degradation in image quality. The algorithm can be applied to real-time image/video applications, such as JPEG2000, MPEG-4 still texture object decoding, and wavelet-based Scalable Video Coding (SVC).[[sponsorship]]IEEE Computer Society, U.S.A.[[notice]]需補會議地點[[conferencetype]]國際[[conferencedate]]20071210~2007121

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