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conference on wavelet applications in signal and image processing viii

作者： Hou, WD Mo, YL Liu, H Hu, HP Shanghai Univ Dept Commun Engn Shanghai 201800 Peoples R China

ISBN: (纸本)0819437646

Video communication aiming at public switched telephone network (PSTN) applied with voice-band modem is attractive because of its low-cost facilities and the wide coverage of PSTN around the world. The key technique of video transmission over PSTN with voice-band modem is very low bit-rate video coding. Video coding based on discrete wavelet transform has become a hot research topic. But while in very low bit-rate video coding applications, the peak signal to noise ratio (PSNR) and the visual quality of image reconstructions are not very satisfactory by using the general orthogonal or biorthogonal wavelet which does not match well with human visual system characteristics. In this paper, a new kind of compact biorthogonal wavelet based on the modulation transfer function for human visual system model is used in very low bit-rate video coding scheme, in which a new improved Goh's three dimension wavelet transform and motion compensation technique are applied. The experimental results indicate that the new coding scheme using the constructed compact biorthogonal wavelet has a good performance in average PSNR, compression ratios and visual quality of image reconstructions when compared to the other motion-compensated two dimension and three dimension coding schemes based on the general biothogonal wavelet transform.

关键词： video coding very low bit-rate compact biothogonal wavelet

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Cone-beam X-ray tomography using continuous wavelet transformation

Cone-beam X-ray tomography using continuous wavelet transfor...

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conference on wavelet applications in signal and image processing viii

作者： Zhao, SY Wang, G Univ Missouri Dept Math & Comp Sci St Louis MO 63130 USA

ISBN: (纸本)0819437646

Recently, medical computed tomography (CT) began a transition from fan-beam to cone-beam geometry with the introduction of multi-row-detector systems. Therefore, cone-beam techniques become important for medical CT. Despite recent advances, the approximate reconstruction method of Feldkamp remains the most commonly employed cone-beam reconstruction algorithm because of its computational efficiency and clinical applicability. Unfortunately, the derivation of the Feldkamp cone-beam reconstruction formula is based on geometric tilted fan heuristic. In this paper, we give a wavelet derivation of the Feldkamp cone-beam reconstruction method. It is found that the Feldkamp algorithm is an outcome of a zero-order approximation to the longitudinal wavelet decomposition of the object function to be reconstructed. Since the approximation is explicitly given, error estimates can be derived analytically. Theoretically, it also arises the possibility of improvement of the Feldkamp cone-beam algorithm.

关键词： continuous wavelet transformation X-ray computed tomography (CT) cone-beam geometry Feldkamp algorithm three-dimensional reconstruction

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A robust image hashing based on discrete wavelet transform 5

A robust image hashing based on discrete wavelet transform

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IEEE International conference on signal and image processing applications (ICSIPA)

作者： Singh, Satendra Pal Bhatnagar, Gaurav Indian Inst Technol Jodhpur Dept Math Jodhpur Rajasthan India

ISBN: (纸本)9781509055593

In this paper, a robust image hashing framework is proposed using image normalization, discrete wavelet transform and singular value decomposition. The stressed motive of the proposed scheme is to obtain a randomize hash sequence which can be used for image authentication and database search. For this purpose, the image is first normalized followed by hash generation in the wavelet domain utilizing the properties of singular value decomposition (SVD). Experimental evaluations demonstrate that the proposed scheme is providing the better robustness and security.

关键词： Discrete wavelet transforms Shearing Robustness Hamming distance Authentication image processing

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image denoising using a local Gaussian scale mixture model in the wavelet domain

Image denoising using a local Gaussian scale mixture model i...

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conference on wavelet applications in signal and image processing viii

作者： Strela, V Portilla, J Simoncelli, E Drexel Univ Dept Math & Comp Sci Philadelphia PA 19104 USA

ISBN: (纸本)0819437646

The statistics of photographic images, when decomposed in a multiscale wavelet basis, exhibit striking nonGaussian behaviors. The joint densities of dusters of wavelet coefficients (corresponding to basis functions at nearby spatial positions, orientations and scales) are well-described as a Gaussian scale mixture: a jointly Gaussian vector multiplied by a hidden scaling variable. We develop a maximum likelihood solution for estimating the hidden variable from an observation of the cluster of coefficients contaminated by additive Gaussian noise. The estimated hidden variable is then used to estimate the original noise-free coefficients. We demonstrate the power of this model through numerical simulations of image denoising.

关键词： natural image statistics wavelet multiresolution Gaussian scale mixture adaptive Wiener filtering denoising

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Architectures for wavelet transforms: A survey

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JOURNAL OF VLSI signal processing SYSTEMS FOR signal image AND VIDEO TECHNOLOGY 1996年第2期14卷 171-192页

作者： Chakrabarti, C Vishwanath, M Owens, RM XEROX CORP PALO ALTO RES CTR COMP SCI LAB PALO ALTO CA 94304 USA PENN STATE UNIV DEPT COMP SCI & ENGN UNIVERSITY PK PA 16802 USA

wavelet transforms have proven to be useful tools for several applications, including signal analysis, signal compression and numerical analysis. This paper surveys the VLSI architectures that have been proposed for computing the Discrete and Continuous wavelet Transforms for I-D and 2-D signals. The architectures are based upon on-line versions of the wavelet transform algorithms. These architectures support single chip implementations and are optimal with respect to both area and time under the word-serial model.

关键词： VLSI circuits

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Attenuation and dispersion of a monopulse in layered and lossy media using an adaptive multiscale wavelet collocation method

Attenuation and dispersion of a monopulse in layered and los...

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conference on wavelet applications in signal and image processing viii

作者： Wang, YZ Wu, RS Wang, WB Univ Calif Santa Cruz Inst Tecton Santa Cruz CA 95064 USA

ISBN: (纸本)0819437646

An adaptive multiscale wavelet collocation method [1] is applied to analyze the attenuation and dispersion of a monopulse in layered and lossy media. From numerical results, it is found that sufficient resolution can be provided in the solution's regions where large gradients and dramatic fluctuation occur. The new wavelet method can thus be regarded as an excellent algorithm for a wave equation's solution with large gradients and dramatic fluctuation.

关键词： wavelet basis wave equation lossy medium attenuation dispersion

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Shift-invariant gibbs free denoising algorithm based on wavelet transform footprints

Shift-invariant gibbs free denoising algorithm based on wave...

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conference on wavelet applications in signal and image processing viii

作者： Dragotti, PL Vetterli, M Ecole Polytech Fed Lausanne LCAV CH-1015 Lausanne Switzerland

ISBN: (纸本)0819437646

In recent years wavelet have had an important impact on signal processing theory and practice. The effectiveness of wavelets is mainly due to their capability of representing piecewise smooth signals with few non-zero coefficients. Away from discontinuities, the inner product between a wavelet (with a number of zero moments) and a smooth function will be either zero or very small.(8) At singular points, a finite number of wavelets concentrated around the discontinuity lead to non-zero inner products. This ability of wavelet transform to pack the main signal information in few large coefficients is behind the success of wavelet based denoising algorithms. Indeed, traditional approaches simply consist in thresholding the noisy wavelet coefficients, so the few large coefficients carrying the essential information are usually kept while small coefficients mainly containing noise are cancelled. However, wavelet denoising suffers of two main drawbacks: it is not shift-invariant and it exhibits pseudo Gibbs phenomenon around discontinuities. In this work, we present a new denoising algorithm which does not present the pseudo Gibbs phenomenon and which is almost shift-invariant even if we do not use a frame expansion. In our analysis we focus on piecewise polynomial functions. For this class of signals we know that, if wavelets have enough vanishing moments, away from discontinuities the wavelet coefficients are exactly zero. Moreover the wavelet coefficients generated by a discontinuity are highly dependent across scales. Therefore, a good denoising algorithm should take advantage of this dependency. We thus introduce the notion of footprints, which are the traces left, by time domain singularities in the wavelet domain. So a footprint is a vector containing all the significant wavelet coefficients generated by a singularity. In our denoising algorithm instead of thresholding the noisy wavelet coefficients independently as in traditional approaches (scalar thresholding), w

关键词： wavelets Denoising wavelet transforms Associative arrays Filtering (signal processing) signal processing Algorithms Linear filtering Reconstruction algorithms signal to noise ratio

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Exponential-quadratic optimal signal reconstruction in noisy filter banks

Exponential-quadratic optimal signal reconstruction in noisy...

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conference on wavelet applications in signal and image processing viii

作者： Vikalo, H Erdogan, AT Hassibi, B Kailath, T Stanford Univ Informat Syst Lab Stanford CA 94305 USA

ISBN: (纸本)0819437646

We consider the design of synthesis filters in noisy filter bank systems using an exponential-quadratic criterion. We assume that the analysis filters have been designed to achieve good coding of the input signal. Then we design the synthesis filters to minimize reconstruction error according to the adopted criterion. When the synthesis filters are restricted to be FIR, the design can be cast as a constrained analytic centering problem. To this end, we first employ standard state-space techniques to obtain a set of H-infinity optimal FIR synthesis filters. Among these, we select the so-called risk-sensitive (or minimum entropy) synthesis filters by additionally minimizing exponential-quadratic cost function. We provide numerical example to illustrate the procedure.

关键词： filter banks H-infinity design risk-sensitive convex optimization

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Rotation invariant texture retrieval using steerable wavelet-domain hidden Markov models

Rotation invariant texture retrieval using steerable wavelet...

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conference on wavelet applications in signal and image processing viii

作者： Do, MN Lozano, AC Vetterli, M Swiss Fed Inst Technol Lab Audiovisual Commun CH-1015 Lausanne Switzerland

ISBN: (纸本)0819437646

A new statistical model for characterizing texture images based on wavelet-domain hidden Markov models and steerable pyramids is presented. The new model is shown to capture well both the subband marginal distributions and the dependencies across scales and orientations of the wavelet descriptors. Once it is trained for an input texture image, the model can be easily steered to characterize that texture at any other orientations. After a diagonalization operation, one obtains a rotation-invariant description of the texture image. The effectiveness of the new model is demonstrated in large test image databases where significant gains in retrieval performance are shown.

关键词： wavelets Databases Data modeling Matrices image retrieval Expectation maximization algorithms Statistical analysis wavelet transforms Statistical modeling Feature extraction

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Karhunen-Loeve multispectral and multiscale image restoration

Karhunen-Loeve multispectral and multiscale image restoratio...

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conference on wavelet applications in signal and image processing viii

作者： Starck, JL Querre, P Donoho, A Stanford Univ Dept Stat Stanford CA 94305 USA

ISBN: (纸本)0819437646

We introduce in this paper the notion of wavelet-Karhunen-Loeve transform (WT-KLT) and apply it to the problem of noise removal. Decorrelating first the data in the spatial domain using the WT and afterwards using the KLT in spectral domain allows us to derive a robust noise modeling in the WT-KLT space, and hence to filter the transformed data in an efficient way. Experiments are performed in order to derive (i) the best way to calculate the covariance matrix in the case of noisy data, (ii) the best method to correct the noisy WT-KLT coefficients. Finally we investigate if the curvelet transform could be an alternative to the wavelet transform for color image filtering.

关键词： wavelets image filtering wavelet transforms Data modeling signal to noise ratio RGB color model Astronomy Interference (communication) Optical filters Principal component analysis

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