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52
Image compression via joint statistical characterization in the wavelet domain
, 1997
"... We develop a statistical characterization of natural images in the wavelet transform domain. This characterization describes the joint statistics between pairs of subband coefficients at adjacent spatial locations, orientations, and scales. We observe that the raw coefficients are nearly decorrelate ..."
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Cited by 237 (27 self)
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We develop a statistical characterization of natural images in the wavelet transform domain. This characterization describes the joint statistics between pairs of subband coefficients at adjacent spatial locations, orientations, and scales. We observe that the raw coefficients are nearly decorrelated, but their magnitudes are highly correlated. A linear magnitude predictor coupled with both multiplicative and additive uncertainties accounts for the joint coefficient statistics of a wide variety of images including photographic images, graphical images, and medical images. In order to directly demonstrate the power of this model, we construct an image coder called EPWIC (Embedded Predictive Wavelet Image Coder), in which subband coefficients are encoded one bitplane at a time using a nonadaptive arithmetic encoder that utilizes probabilities calculated from the model. Bitplanes are ordered using a greedy algorithm that considers the MSE reduction per encoded bit. The decoder uses the statistical model to predict coefficient values based on the bits it has received. The ratedistortion performance of the coder compares favorably with the current best image coders in the literature. 1
Spacefrequency Quantization for Wavelet Image Coding
, 1997
"... Recently, a new class of image coding algorithms coupling standard scalar quantization of frequency coefficients with treestructured quantization (related to spatial structures) has attracted wide attention because its good performance appears to confirm the promised efficiencies of hierarchical re ..."
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Cited by 172 (15 self)
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Recently, a new class of image coding algorithms coupling standard scalar quantization of frequency coefficients with treestructured quantization (related to spatial structures) has attracted wide attention because its good performance appears to confirm the promised efficiencies of hierarchical representation [1, 2]. This paper addresses the problem of how spatial quantization modes and standard scalar quantization can be applied in a jointly optimal fashion in an image coder. We consider zerotree quantization (zeroing out treestructured sets of wavelet coefficients) and the simplest form of scalar quantization (a single common uniform scalar quantizer applied to all nonzeroed coefficients), and we formalize the problem of optimizing their joint application and we develop an image coding algorithm for solving the resulting optimization problem. Despite the basic form of the two quantizers considered, the resulting algorithm demonstrates coding performance that is competitive (often...
Image Coding based on Mixture Modeling of Wavelet Coefficients and a Fast EstimationQuantization Framework
, 1997
"... We introduce a new image compression paradigm that combines compression efficiency with speed, and is based on an independent "infinite" mixture model which accurately captures the spacefrequency characterization of the wavelet image representation. Specifically, we model image wavelet co ..."
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Cited by 163 (11 self)
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We introduce a new image compression paradigm that combines compression efficiency with speed, and is based on an independent "infinite" mixture model which accurately captures the spacefrequency characterization of the wavelet image representation. Specifically, we model image wavelet coefficients as being drawn from an independent Generalized Gaussian distribution field, of fixed unknown shape for each subband, having zero mean and unknown slowly spatiallyvarying variances. Based on this model, we develop a powerful "on the fly" EstimationQuantization (EQ) framework that consists of: (i) first finding the MaximumLikelihood estimate of the individual spatiallyvarying coefficient field variances based on causal and quantized spatial neighborhood contexts; and (ii) then applying an offline RateDistortion (RD) optimized quantization /entropy coding strategy, implemented as a fast lookup table, that is optimally matched to the derived variance estimates. A distinctive feature of o...
InformationTheoretic Analysis of Interscale and Intrascale Dependencies Between Image Wavelet Coefficients
 IEEE Transactions on Image Processing
, 2001
"... This paper presents an informationtheoretic analysis of statistical dependencies between image wavelet coefficients. The dependencies are measured using mutual information, which has a fundamental relationship to data compression, estimation, and classification performance. ..."
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Cited by 96 (1 self)
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This paper presents an informationtheoretic analysis of statistical dependencies between image wavelet coefficients. The dependencies are measured using mutual information, which has a fundamental relationship to data compression, estimation, and classification performance.
Multiple Description Wavelet Based Image Coding
, 1998
"... We consider the problem of coding images for transmission over errorprone channels. The impairments we target are transient channel shutdowns, as would occur in a packet network when a packet is lost, or in a wireless system during a deep fade: when data is delivered it is assumed to be errorfree, ..."
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Cited by 78 (8 self)
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We consider the problem of coding images for transmission over errorprone channels. The impairments we target are transient channel shutdowns, as would occur in a packet network when a packet is lost, or in a wireless system during a deep fade: when data is delivered it is assumed to be errorfree, but some of the data may never reach the receiver. The proposed algorithms are based on a combination of multiple description scalar quantizers with techniques successfully applied to the construction of some of the most ecient subband coders. A given image is encoded into multiple independent packets of roughly equal length. When packets are lost, the quality of the approximation computed at the receiver depends only on the number of packets received, but does not depend on exactly which packets are actually received. When compared with previously reported results on the performance of robust image coders based on multiple descriptions, on standard test images, our coders attain s...
Line Based, Reduced Memory, Wavelet Image Compression
 in Proc. IEEE Data Compression Conference, (Snowbird, Utah
, 1998
"... In this work we propose a novel algorithm for wavelet based image compression with very low memory requirements. The wavelet transform is performed progressively and we only require that a reduced number of lines from the original image be stored at any given time. The result of the wavelet trans ..."
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Cited by 20 (2 self)
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In this work we propose a novel algorithm for wavelet based image compression with very low memory requirements. The wavelet transform is performed progressively and we only require that a reduced number of lines from the original image be stored at any given time. The result of the wavelet transform is the same as if wewere operating on the whole image, the only di#erence being that the coe#cients of di#erent subbands are generated in an interleaved fashion. We begin encoding the #interleaved# wavelet coe#cients as soon as they become available. We classify each new coe#cient in one of several classes, each corresponding to a di#erent probability model, with the models being adapted on the #y for each image. Our scheme is fully backward adaptive and it relies only on coe#cients that have already been transmitted. Our experiments demonstrate that our coder is still very competitive with respect to similar state of the art coders, such as #1, 2#. Note that schemes based on z...
Progressive Image Coding Using Trellis Coded Quantization
, 1997
"... In this paper, we present coding techniques that enable progressive transmission when trellis coded quantization (TCQ) is applied to wavelet coefficients. A method for approximately inverting TCQ in the absence of least signficant bits is developed. Results are presented using different rate allocat ..."
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Cited by 17 (3 self)
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In this paper, we present coding techniques that enable progressive transmission when trellis coded quantization (TCQ) is applied to wavelet coefficients. A method for approximately inverting TCQ in the absence of least signficant bits is developed. Results are presented using different rate allocation strategies (optimal rate allocation and constant quantization step size) and different entropy coders (the SPIHT entropy coder and a bit plane coder). The waveletTCQ coder using optimal bit allocation and a progressively decodable bit plane coder yields excellent coding efficiency while supporting progressive modes analogous to those available in JPEG. EDICS: IP1.1 Coding Permission to publish this abstract separately is granted. This work was supported in part by the National Science Foundation under Grant No. NCR9258374. y A. Bilgin and M. W. Marcellin are with the Department of Electrical and Computer Engineering, The University of Arizona, Tucson, AZ 85721. P. J. Sementilli is ...
Multipledescription wavelet based image coding
 in Proc. IEEE Int. Conf. Image Process
, 1998
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Multiple description trelliscoded quantization
 IEEE Trans. Commun
, 1999
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