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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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Exploring the power of wavelet analysis

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IEEE COMPUTER applications IN POWER 1996年第4期9卷 37-41页

作者： Galli, AW Heydt, GT Ribeiro, PF ARIZONA STATE MUSEUM NSFCTR POWER ENGNTEMPEAZ

wavelets are a recently developed mathematical tool for signal analysis. Informally, a wavelet is a short-term duration wave. wavelets are used as a kernel function in an integral transform, much in the same way that sines and cosines are used in Fourier analysis or the Walsh functions in Walsh analysis. To date, the primary application of wavelets has been in the areas of signal processing, image compression, subband coding, medical imaging, data compression, seismic studies, denoising data, computer vision and sound synthesis. Here, the authors describe how wavelets may be used in the analysis of power system transients using computer implementation.

关键词： wavelet analysis image coding signal analysis Kernel Fourier transforms wavelet transforms Application software Acoustic signal processing Biomedical imaging Data compression

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image data compression with three-directional splines

Image data compression with three-directional splines

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Conference on wavelet applications in signal and image processing viii

作者： Charina, M Conti, C Jetter, K Univ Hohenheim Inst Angew Math & Stat D-70593 Stuttgart Germany

ISBN: (纸本)0819437646

In this paper we consider a new method for image data compression. It is based on three-directional spline functions of low degree, viz. piecewise constant functions, and piecewise cubic C-1-functions. In the first case a Haar wavelet type decomposition can be derived, and combined with standard thresholding techniques. In the second case, due to the fact that a spline basis is given by convolution products, the wavelet decomposition and thresholding can be computed on one factor of the convolution product only. Performance of the proposed method is discussed in section 3 where the reconstructed pictures are compared with the ones produced by the analogous decomposition methods provided by the MATLAB wavelet toolbox.

关键词： three-directional splines wavelets data compression thresholding cardinal interpolation

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Robust technique for image descreening based on the wavelet transform

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IEEE TRANSACTIONS ON signal processing 1998年第4期46卷 1179-1184页

作者： Luo, JB de Queiroz, R Fan, ZG Xerox Corp Digital Imaging Technol Ctr Webster NY 14580 USA

In this correspondence, a novel wavelet-based approach to recover continuous-tone (contone) images from halftone images is presented. wavelet decomposition of the halftone image facilitates a series of spatial and frequency selective processing to preserve most of the original image contents while eliminating the halftone noise. Furthermore, optional nonlinear filtering can be applied as a postprocessing stage to create the final aesthetic contone image. This approach lends itself to practical applications since it is independent of parameter estimation and, hence, universal to all types of halftoned images, including those obtained by scanning printed halftones.

关键词： Robustness wavelet transforms Frequency Digital images Optimization methods Continuous wavelet transforms Filtering image processing Constraint optimization Smoothing methods

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Asymptotically optimal blind estimation of multichannel images

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IEEE TRANSACTIONS ON image processing 2006年第4期15卷 992-1007页

作者： Atkinson, I Kamalabadi, F Mohan, S Jones, DL Univ Illinois Dept Elect & Comp Engn Urbana IL 61801 USA Univ Illinois Coordinated Sci Lab Urbana IL 61801 USA

Optimal estimation of a two-dimensional (2-D) multichannel signal ideally decorrelates the data in both channel and space and weights the resulting coefficients according to their SNR. Many scenarios exist where the required second-order signal and noise statistics are not known in which the decorrelation is difficult or expensive to calculate. An asymptotically optimal estimation scheme proposed here uses a 2-D discrete wavelet transform to approximately decorrelate the signal in space and the discrete Fourier transform to decorrelate between channels. The coefficient weighting is replaced with a wavelet-domain thresholding operation to result in an efficient estimation scheme for both stationary and nonstationary signals. in contrast to optimal estimation, this new scheme does not require second-order signal statistics, making it well suited to many applications. In addition to providing vastly improved visual quality, the new estimator typically yields signal-to-noise ratio gains 12 dB or higher for hyperspectral imagery and functional magnetic resonance images.

关键词： estimation image processing multidimensional signal processing wavelet transforms

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wavelet-based method for image filtering using scale-space continuity

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JOURNAL OF ELECTRONIC IMAGING 2001年第2期10卷 511-520页

作者： Jung, CR Scharcanski, J Univ Vale Rio dos Sinos UNISINOS Ctr Ciencias Exatas & Tecnol BR-93022000 Sao Leopoldo RS Brazil Univ Fed Rio Grande do Sul Inst Informat BR-91501970 Porto Alegre RS Brazil

This paper proposes a novel technique to reduce noise while preserving edge sharpness during image filtering. This method is based on the image multiresolution decomposition by a discrete wavelet transform, given a proper wavelet basis. In the transform space, edges are implicitly located and preserved, at the same time that image noise is filtered out. At each resolution level, geometric continuity is used to preserve edges that are not isolated Finally, we compare consecutive levels to preserve edges having continuity along scales. As a result, the proposed technique produces a filtered version of the original image, where homogeneous regions appear separated by well-defined edges. Possible applications include image presegmentation and image denoising. (C) 2001 SPIE and IS&T.

关键词： image filtering signal to noise ratio wavelets wavelet transforms Edge detection Electronic filtering image processing image segmentation signal processing Synthetic aperture radar

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Performance analysis of wavelets in embedded zerotree-based lossless image coding schemes

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IEEE TRANSACTIONS ON signal processing 1999年第3期47卷 884-889页

作者： Ramaswamy, VN Ranganathan, N Namuduri, KR Lucent Technol Bell Labs Holmdel NJ 07733 USA Clark Atlanta Univ Ctr Theoret Studies Phys Syst Atlanta GA 30314 USA

In this correspondence, we present a modification to the scanning approach in the set partitioning algorithm proposed by Said and Pearlman to exploit the correlation in a local neighborhood. The wavelet filters are characterized based on the wavelet coefficients obtained after the wavelet transform. Two new criteria are proposed for evaluating the performance of wavelets in lossless image compression applications: cumulative zerotree count and monotone spectral ordering of subbands produced after wavelet transform in a multiresolution scheme. Several wavelet filters are evaluated to test the evaluation criteria. The experimental results are presented to justify the proposed performance criteria.

关键词： embedded zerotree wavelet lossless image coding performance analysis subband coding

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HS remote sensing image restoration using fusion with MS images by EM algorithm

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IET signal processing 2017年第1期11卷 95-103页

作者： Ansari, Amir Danyali, Habibollah Helfroush, Mohammad Sadegh Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran

Remote sensing images are widely used for different areas from mineral exploration to agricultural applications and poor quality of hyperspectral (HS) images will directly have adverse effect on these applications. In this study, a method is proposed to restore degraded HS images. To achieve this aim, another multispectral (MS) observation of the same scene is supposed to be available and restoration is fulfilled by fusion of HS images and MS images. The proposed method gains maximum a posteriori estimation and is based on expectation maximisation algorithm. Deblurring and denoising are performed separately. Deblurring is done in spatial domain via non-overlapping blocks, whereas denoising is implemented in wavelet domain. To represent the coefficients in wavelet domain, instead of multinormal model, Gaussian scale mixture is exploited. The proposed method is validated on airborne visible/infrared imaging spectrometer (AVIRIS) and HS digital imagery collection experiment (HYDICE) databases and experimental results signify that the proposed method outperforms state-of-the-art techniques cited in the literature and signal-to-noise ratio is improved as much as 15.71dB for Moffett database and 16.26dB for HYDICE database.

关键词： remote sensing image restoration image fusion hyperspectral imaging expectation-maximisation algorithm image denoising wavelet transforms Gaussian processes mixture models geophysical image processing HS remote sensing image restoration MS images EM algorithm mineral exploration agricultural application hyperspectral image quality degraded HS image restoration multispectral observation HS image-MS image fusion maximum a posteriori estimation expectation maximisation algorithm deblurring denoising spatial domain nonoverlapping blocks wavelet domain multinormal model Gaussian scale mixture airborne visible-infrared imaging spectrometer HS digital imagery collection experiment HYDICE database signal-to-noise ratio Moffett database

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Multiresolution wedgelet transform for image processing

Multiresolution wedgelet transform for image processing

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wavelet applications in signal and image processing viii

作者： Claypoole Jr., Roger L. Baraniuk, Richard G. Air Force Inst of Technology Wright-Patterson Air Force Base United States

Edges in images convey a great deal of information, but wavelet transforms do not provide an economical representation. Thus, popular wavelet-based compression and restoration techniques perform poorly in the presence of edges. We present here a new multiresolution wedgelet transform based on the lifting construction. This transform provides an economical edge representation and thus offers the potential for improved image processing. We demonstrate this potential with applications in image denoising.

关键词： image reconstruction

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image compression with adaptive Haar-Walsh tilings

Image compression with adaptive Haar-Walsh tilings

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Conference on wavelet applications in signal and image processing viii

作者： Lindberg, M Villemoes, LF Abo Akad Univ Dept Math Turku Finland

ISBN: (纸本)0819437646

We perform adaptive joint space and frequency tilings including all levels in the Haar-Walsh wavelet packet tree for two-dimensional signals. The method gives surprisingly good results in terms of nonlinear approximation. The visual quality of the compressed images with this method is the same as the quality using twice the number of coefficients for wavelets and standard wavelet packets when Haar filters are used. When all levels are allowed the cost for description of the location of the winning coefficients is not negligible. A tiling information vector is introduced for description of the chosen basis and the original image can be easily and quickly reconstructed using this information. For image compression this tiling information vector is compressed to only those nodes which correspond to kept coefficients, and this makes the adaptive scheme competitive.

关键词： anisotropic wavelet packets best basis space-frequency transform Haar filter Walsh functions image coding

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