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206
Factoring wavelet transforms into lifting steps
 J. Fourier Anal. Appl
, 1998
"... ABSTRACT. This paper is essentially tutorial in nature. We show how any discrete wavelet transform or two band subband filtering with finite filters can be decomposed into a finite sequence of simple filtering steps, which we call lifting steps but that are also known as ladder structures. This dec ..."
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Cited by 434 (7 self)
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ABSTRACT. This paper is essentially tutorial in nature. We show how any discrete wavelet transform or two band subband filtering with finite filters can be decomposed into a finite sequence of simple filtering steps, which we call lifting steps but that are also known as ladder structures. This decomposition corresponds to a factorization of the polyphase matrix of the wavelet or subband filters into elementary matrices. That such a factorization is possible is wellknown to algebraists (and expressed by the formula); it is also used in linear systems theory in the electrical engineering community. We present here a selfcontained derivation, building the decomposition from basic principles such as the Euclidean algorithm, with a focus on applying it to wavelet filtering. This factorization provides an alternative for the lattice factorization, with the advantage that it can also be used in the biorthogonal, i.e, nonunitary case. Like the lattice factorization, the decomposition presented here asymptotically reduces the computational complexity of the transform by a factor two. It has other applications, such as the possibility of defining a waveletlike transform that maps integers to integers. 1.
The Lifting Scheme: A Construction Of Second Generation Wavelets
, 1997
"... . We present the lifting scheme, a simple construction of second generation wavelets, wavelets that are not necessarily translates and dilates of one fixed function. Such wavelets can be adapted to intervals, domains, surfaces, weights, and irregular samples. We show how the lifting scheme leads to ..."
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Cited by 373 (16 self)
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. We present the lifting scheme, a simple construction of second generation wavelets, wavelets that are not necessarily translates and dilates of one fixed function. Such wavelets can be adapted to intervals, domains, surfaces, weights, and irregular samples. We show how the lifting scheme leads to a faster, inplace calculation of the wavelet transform. Several examples are included. Key words. wavelet, multiresolution, second generation wavelet, lifting scheme AMS subject classifications. 42C15 1. Introduction. Wavelets form a versatile tool for representing general functions or data sets. Essentially we can think of them as data building blocks. Their fundamental property is that they allow for representations which are efficient and which can be computed fast. In other words, wavelets are capable of quickly capturing the essence of a data set with only a small set of coefficients. This is based on the fact that most data sets have correlation both in time (or space) and frequenc...
Multiple Description Coding: Compression Meets the Network
, 2001
"... This article focuses on the compressed representations of the pictures ..."
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Cited by 287 (7 self)
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This article focuses on the compressed representations of the pictures
Nonlinear wavelet transforms for image coding via lifting
, 2003
"... We investigate central issues such as invertibility, stability, synchronization, and frequency characteristics for nonlinear wavelet transforms built using the lifting framework. The nonlinearity comes from adaptively choosing between a class of linear predictors within the lifting framework. We al ..."
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Cited by 91 (3 self)
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We investigate central issues such as invertibility, stability, synchronization, and frequency characteristics for nonlinear wavelet transforms built using the lifting framework. The nonlinearity comes from adaptively choosing between a class of linear predictors within the lifting framework. We also describe how earlier families of nonlinear filter banks can be extended through the use of prediction functions operating on a causal neighborhood of pixels. Preliminary compression results for model and realworld images demonstrate the promise of our techniques.
Interactive rendering of large volume data sets
 In Proceedings of Visualization 2002
, 2002
"... We present a new algorithm for rendering very large volume data sets at interactive framerates on standard PC hardware. The algorithm accepts scalar data sampled on a regular grid as input. The input data is converted into a compressed hierarchical wavelet representation in a preprocessing step. Dur ..."
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Cited by 82 (5 self)
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We present a new algorithm for rendering very large volume data sets at interactive framerates on standard PC hardware. The algorithm accepts scalar data sampled on a regular grid as input. The input data is converted into a compressed hierarchical wavelet representation in a preprocessing step. During rendering, the wavelet representation is decompressed onthefly and rendered using hardware texture mapping. The level of detail used for rendering is adapted to the local frequency spectrum of the data and its position relative to the viewer. Using a prototype implementation of the algorithm we were able to perform an interactive walkthrough of large data sets such as the visible human on a single oftheshelf PC.
An overview of the JPEG2000 still image compression standard
 Signal Processing: Image Communication
, 2002
"... In 1996, the JPEGcommittee began to investigate possibilities for a new still image compression standard to serve current and future applications. This initiative, which was named JPEG2000, has resulted in a comprehensive standard (ISO 154447ITUT Recommendation T.800) that is being issued in six pa ..."
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Cited by 76 (0 self)
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In 1996, the JPEGcommittee began to investigate possibilities for a new still image compression standard to serve current and future applications. This initiative, which was named JPEG2000, has resulted in a comprehensive standard (ISO 154447ITUT Recommendation T.800) that is being issued in six parts. Part 1, in the same vein as the JPEG baseline system, is aimed at minimal complexity and maximal interchange and was issued as an International Standard at the end of 2000. Parts 2–6 define extensions to both the compression technology and the file format and are currently in various stages of development. In this paper, a technical description of Part 1 of the JPEG2000 standard is provided, and the rationale behind the selected technologies is explained. Although the JPEG2000 standard only specifies the decoder and the codesteam syntax, the discussion will span both encoder and decoder issues to provide a better
Multiple Description Coding Using Pairwise Correlating Transforms
 IEEE Trans. Image Processing
, 1999
"... The objective of multiple description coding (MDC) is to encode a source into two (or more) bitstreams supporting two quality levels of decoding. A highquality reconstruction should be decodable from the two bitstreams together, while lower, but still acceptable, quality reconstructions should b ..."
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Cited by 68 (1 self)
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The objective of multiple description coding (MDC) is to encode a source into two (or more) bitstreams supporting two quality levels of decoding. A highquality reconstruction should be decodable from the two bitstreams together, while lower, but still acceptable, quality reconstructions should be decodable from either of the two individual bitstreams. This paper describes techniques for meeting MDC objectives in the framework of standard transformbased image coding through the design of pairwise transforms.
Generalized multiple description coding with correlating transforms
 IEEE Trans. Inform. Theory
, 2001
"... Abstract—Multiple description (MD) coding is source coding in which several descriptions of the source are produced such that various reconstruction qualities are obtained from different subsets of the descriptions. Unlike multiresolution or layered source coding, there is no hierarchy of descriptio ..."
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Cited by 61 (2 self)
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Abstract—Multiple description (MD) coding is source coding in which several descriptions of the source are produced such that various reconstruction qualities are obtained from different subsets of the descriptions. Unlike multiresolution or layered source coding, there is no hierarchy of descriptions; thus, MD coding is suitable for packet erasure channels or networks without priority provisions. Generalizing work by Orchard, Wang, Vaishampayan, and Reibman, a transformbased approach is developed for producing descriptions of antuple source,. The descriptions are sets of transform coefficients, and the transform coefficients of different descriptions are correlated so that missing coefficients can be estimated. Several transform optimization results are presented for memoryless Gaussian sources, including a complete solution of the aP, aPcase with arbitrary weighting of the descriptions. The technique is effective only when independent components of the source have differing variances. Numerical studies show that this method performs well at low redundancies, as compared to uniform MD scalar quantization. Index Terms—Erasure channels, integertointeger transforms, packet networks, robust source coding.
An overview of JPEG 2000
 in Proc. IEEE Data Compression Conf., Snowbird, UT
, 2000
"... JPEG2000 is an emerging standard for still image compression. This paper provides a brief history of the JPEG2000 standardization process, an overview of the standard, and some description of the capabilities provided by the standard. Part I of the JPEG2000 standard specifies the minimum complian ..."
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Cited by 60 (2 self)
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JPEG2000 is an emerging standard for still image compression. This paper provides a brief history of the JPEG2000 standardization process, an overview of the standard, and some description of the capabilities provided by the standard. Part I of the JPEG2000 standard specifies the minimum compliant decoder, while Part II describes optional, valueadded extensions. Although the standard specifies only the decoder and bitstream syntax, in this paper we describe JPEG2000 from the point of view of encoding. We take this approach, as we believe it is more amenable to a compact description more easily understood by most readers. 1
Lossless Image Compression Using Integer To Integer Wavelet Transforms
 In International Conference on Image Processing (ICIP
, 1997
"... Invertible wavelet transforms that map integers to integers are important for lossless representations. In this paper, we present an approach to build integer to integer wavelet transforms based upon the idea of factoring wavelet transforms into lifting steps. This allows the construction of an inte ..."
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Cited by 47 (0 self)
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Invertible wavelet transforms that map integers to integers are important for lossless representations. In this paper, we present an approach to build integer to integer wavelet transforms based upon the idea of factoring wavelet transforms into lifting steps. This allows the construction of an integer version of every wavelet transform. We demonstrate the use of these transforms in lossless image compression. 1 INTRODUCTION Highfidelity images generated from studioquality video, medical images, seismic data, satellite images, and images scanned from manuscripts for preservation purposes typically demand lossless encoding. Yet, the huge datasize prohibits fast distribution of data. There is thus a need to seek encoding methods that can support storage and transmission of images at a spectrum of resolutions and encoding fidelities, from lossy to lossless, for progressive delivery and for different endusers' needs. In recent years, wavelet transforms have been successfully used for ...