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Variable sampling of the empirical mode decomposition of two-dimensional signals

INTERNATIONAL JOURNAL OF wavelets MULTIRESOLUTION AND INFORMATION processing 2005年第3期3卷 435-452页

作者： Linderhed, A Swedish Def Res Agcy SE-58111 Linkoping Sweden

Previous work on empirical mode decomposition in two dimensions typically generates a residue with many extrema, points. In this paper we propose an improved method to decompose an image into a number of intrinsic mode functions and a residue image with a minimum number of extrema, points. We further propose a method for the variable sampling of the two-dimensional empirical mode decomposition. Since traditional frequency concept is not applicable in this work, we introduce the concept of empiquency, shortform for empirical mode frequency, to describe the signal oscillations. The very special properties of the intrinsic mode functions are used for variable sampling in order to reduce the number of parameters to represent the image. This is done blockwise using the occurrence of extrema points of the intrinsic mode function to steer the sampling rate of the block. A method of using overlapping 7 x 7 blocks is introduced to overcome blocking artifacts and to further reduce the number of parameters required to represent the image. The results presented here shows that an image can be successfully decomposed into a number of intrinsic mode functions and a residue image with a minimum number of extrema points. The results also show that subsampling offers a way to keep the total number of samples generated by empirical mode decomposition approximately equal to the number of pixels of the original image.

关键词： empirical mode decomposition time-frequency analysis image processing sampling sequency empiquency

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The dual-tree complex wavelet transform

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IEEE signal processing MAGAZINE 2005年第6期22卷 123-151页

作者： Selesnick, IW Baraniuk, RG Kingsbury, NG Rice Univ Houston TX 77251 USA Univ Cambridge Cambridge CB2 1TN England

The dual-tree CWT is a valuable enhance- ment of the traditional real wavelet trans- form that is nearly shift invariant and, in higher dimensions, directionally selective. Since the real and imaginary parts of the dual-tree CWT are, in fact, conventional real wavelet transforms, the CWT benefits from the vast theoretical, practical, and computational resources that have been developed for the standard DWT. For example, software and hardware developed for implementation of the real DWT can be used directly for the CWT. But, in addition, the magnitude and phase of CWT coefficients can be exploited to develop new effective wavelet- based algorithms, especially for applications for which the DWT is unsuited or underperforms. MATLAB software for the dual-tree complex wavelet transform (and related algorithms) is available at the following locations on the web: http://***/waveletsoftware/, http://www- ***/ ngk/, and http://***/.

关键词： Wavelet transforms Discrete wavelet transforms Continuous wavelet transforms Wavelet analysis signal processing Filter bank Low pass filters image processing Multidimensional signal processing Geophysical signal processing

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A new image texture extraction algorithm based on Matching Pursuit Gabor wavelets

A new image texture extraction algorithm based on Matching P...

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2005 IEEE International Conference on Acoustics, Speech, and signal processing, ICASSP '05

作者： Yaghoobi, M. Rabiee, H.R. Ghanbari, M. Shamsollahi, M.B. Digital Media Lab. Sharif University of Technology Department of Electronic Systems Engineering University of Essex United Kingdom Department of Electrical Engineering Sharif University of Technology

ISBN: (纸本)0780388747

Feature vector extraction, based on local image texture, is a primitive algorithm for many other applications, like segmentation, clustering and identification. If these feature vectors are a good match to the human visual system (HVS), we can expect to get the appropriate results by using them. Gabor filters has been used for this purpose successfully. In this paper we introduce a novel refinement, with the use of Matching Pursuit (MP) to improve the Gabor based texture feature extractor. With this improvement, we show that the separability of different textures will increase. Another consideration in this work is computation complexity. Therefore, we limit the basis function set to reduce MP computation time. © 2005 IEEE.

关键词： Textures

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Parametrically controlled noise shaping in variable state-step-back pseudo-Trellis SDM

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IEE PROCEEDINGS-VISION image AND signal processing 2005年第1期152卷 87-96页

作者： Hawksford, MOJ Univ Essex Colchester CO4 3SQ Essex England

Progress is reported in parametrically controlled noise shaping sigma delta modulator (SDM) design. As this SDM structure can provide a higher SNR than normal SDM structures, Philips Research Laboratories questioned whether further improvement could be obtained using techniques inspired by the Trellis SDM. Simulations are used here to illustrate the performance of a parametrically controlled pseudo-Trellis SDM. The technique uses uniquely a variable state step-back approach to mediate loop behaviour that is shown to achieve robust stability in the presence of aggressive noise shaping and high level signals. Comparisons are made with traditional SDM structures and LPCM systems for high-resolution audio applications.

关键词： NOISE TRELLIS-coded modulation PARAMETER estimation signal theory (Telecommunication) MODULATION (Electronics) MODULATION theory ESTIMATION theory

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Resolution improvement and detail enhancement for computed tomography scout images

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JOURNAL OF ELECTRONIC IMAGING 2005年第1期14卷 013003.1-013003.1页

作者： Zheng, YF Wachowiak, MP Elmaghraby, AS Univ Louisville Dept Psychol & Brain Sci Louisville KY 40292 USA Univ Louisville Dept Comp Sci & Engn Louisville KY 40292 USA

New applications currently demand utilizing computed tomography (CT) scout images for diagnostic purposes. However, many CT scout images cannot be used diagnostically due to their poor resolution, particularly in the direction of table movement, and loss of detail when displayed with one view. We present two methods to address these two problems. First, spatial resolution generally can be improved with image restoration techniques. Based on the principles of Wiener filtering and inverse filtering, a modified Wiener filtering approach is presented in the frequency domain. The concept of an equivalent target point spread function is also introduced, which makes the restoration process steerable. Consequently, balancing resolution improvement with noise suppression is facilitated. Relevant experiments compare the image quality with traditional inverse filtering and Wiener filtering. The modified Wiener filtering method has been shown to restore the scout image with higher resolution and lower noise. In addition, CT scout images have a wide dynamic range, from 0 to 105 intensity values. They are difficult to display in full detail with only 8 bits (256 intensities). An image fusion approach is developed to preserve and enhance details of CT scout images. The enhanced image is obtained by high-boosting one fused image from another, both of which are computed by fusing a set of preenhanced subimages which derived from the original, using different fusion rules. image fusion is performed pixel by pixel by the discrete wavelet transform. Final experiments compare the image quality of the resolution-improved and detail-enhanced image and the noise level with those of the original image. Results show that more details, easily observed by a radiologist, are present in the restored and enhanced image than in the original. 0 2005 SPIE and IS&T.

关键词： image fusion image enhancement Finite element methods image resolution Electronic filtering Discrete wavelet transforms Point spread functions image processing wavelets Computed tomography

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WCAM: Smart encoding for wireless surveillance

WCAM: Smart encoding for wireless surveillance

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Conference on image and Video Communications and processing 2005

作者： Meessen, J Parisot, C Le Barz, C Nicholson, D Delaigle, JF Multitel Asbl Mons Belgium

ISBN: (纸本)0819456586

In this paper, we present an integrated system for smart encoding in video surveillance. This system, developed within the European IST WCAM project, aims at defining an optimized JPEG 2000 codestream organization directly based on the semantic content of the video surveillance analysis module. The proposed system produces a fully compliant Motion JPEG 2000 stream that contains regions of interest (typically mobile objects) data in a separate layer than regions of less interest (e.g. static background). First the system performs a real-time unsupervised segmentation of mobiles in each frame of the video. The smart encoding, module uses these regions of interest maps in order to construct a Motion JPEG 2000 codestream, that allows an optimized rendering of the video surveillance stream in low bandwidth wireless applications, allocating more quality to mobiles than for the background. Our integrated system improves the coding representation of the video content without data overhead. It can also be used in applications requiring selective scrambling of regions of interest as well as for any other application dealing with regions of interest.

关键词： Video surveillance Video image segmentation image compression Computer programming Video compression image quality Video coding Surveillance wavelets

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image denoising using neighbouring wavelet coefficients

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INTEGRATED COMPUTER-AIDED ENGINEERING 2005年第1期12卷 99-107页

作者： Chen, GY Bui, TD Krzyzak, A Concordia Univ Dept Comp Sci Montreal PQ H3G 1M8 Canada

The denoising of a natural image corrupted by Gaussian noise is a classical problem in signal or image processing. Donoho and his coworkers at Stanford pioneered a wavelet denoising scheme by thresholding the wavelet coefficients arising from the standard discrete wavelet transform. This work has been widely used in science and engineering applications. However, this denoising scheme tends to kill too many wavelet coefficients that might contain useful image information. In this paper. we propose one wavelet image thresholding scheme by incorporating neighbouring coefficients for both translation-invariant (TI) and non-TI cases. This approach is valid because a large wavelet coefficient will probably have large wavelet coefficients at its neighbour locations. Experimental results show that our algorithm is better than VisuShrink and the TI image denoising method developed by Yu et al. We also investigate different neighbourhood sizes and find that a size of 3 x 3 or 5 x 5 is the best among all window sizes.

关键词： image information Wavelet coefficients image denoising method Noise reduction Neighbor image denoising Gaussian noise

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Another FIR lattice structure

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INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND applications 2005年第4期33卷 347-351页

作者： Roy, SCD Vishwanath, R Indian Inst Technol Dept Elect Engn New Delhi 110016 India

A new two multiplier FIR lattice structure is derived by using the digital two-pair concept, which produces two transfer functions H-i(z) and H-i'(z) having the complementary relationship H-i'(z) = z(-i) H-i(-z (-1)), in contrast to the mirror image relationship, i.e. H-i'(z) = z(-i)H(i)(z(-1)) satisfied in the conventional FIR lattice structure. The new structure should be useful in crossover networks as well as in multirate signal processing. Copyright (c) 2005 John Wiley & Sons, Ltd.

关键词： FIR lattice digital complementary filters digital signal processing

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Complete-to-overcomplete discrete wavelet transforms: Theory and applications

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IEEE TRANSACTIONS ON signal processing 2005年第4期53卷 1398-1412页

作者： Andreopoulos, Y Munteanu, A Van der Auwera, G Cornelis, JPH Schelkens, P Free Univ Brussels Dept Elect & Informat Proc ETRO B-1050 Brussels Belgium

A new transform is proposed that derives the overcomplete discrete wavelet transform (ODWT) subbands from the critically sampled DWT subbands (complete representation). This complete-to-overcomplete DWT (CODWT) has certain advantages in comparison to the conventional approach that performs the inverse DWT to reconstruct the input signal, followed by the a-trous or the lowband shift algorithm. Specifically, the computation of the input signal is not required. As a result, the minimum number of downsampling operations is performed and the use of upsampling is avoided. The proposed CODWT computes the ODWT subbands by using a set of prediction-filter matrices and filtering-and-downsampling operators applied to the DWT. This formulation demonstrates a clear separation between the single-rate and multirate components of the transform. This can be especially significant when the CODWT is used in resource-constrained environments, such as resolution-scalable image and video codecs. To illustrate the applicability of the proposed transform in these emerging applications, a new scheme for the transform-calculation is proposed, and existing coding techniques that benefit from its usage are surveyed. The analysis of the proposed CODWT in terms of arithmetic complexity and delay reveals significant gains as compared with the conventional approach.

关键词： complexity reduction overcomplete discrete wavelet transforms scalable image and video coding shift invariance

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Blind source separation: New tools for extraction of source signals and denoising

Blind source separation: New tools for extraction of source ...

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Conference on Independent Component Analyses, wavelets, Unsupervised Smart Sensors, and Neural Networks III

作者： Cichocki, A RIKEN Brain Sci Inst Lab Adv Brain Signal Proc Wako Saitama 3510198 Japan

ISBN: (纸本)0819458031

Blind source separation (BSS) and related methods such as independent component analysis (ICA) and their extensions or sparse component analysis (SCA) refers to wide class of problems in signal and image processing, when one needs to extract the underlying sources from a set of mixture. The goal of BSS can be considered as estimation of true physical sources and parameters of a mixing system, while objective of generalized component analysis (GCA) is finding a new reduced or hierarchical and structured representation for the observed (sensor) multidimensional data that can be interpreted as physically meaningful coding or blind signal decompositions. These methods are generally based on a wide class of unsupervised learning algorithms and they found potential applications in many areas from engineering to neuroscience. The recent trends in blind source separation and generalized component analysis is to consider problems in the framework of matrix factorization or more general signals decomposition with probabilistic generative and tree structured graphical models and exploit some priori knowledge about true nature and structure of latent (hidden) components or sources such as spatio-temporal decorrelation, statistical independence, sparsity, nonnegativity, smoothness or lowest possible complexity. The key issue is to find a such transformation or coding which has true physical meaning and interpretation. In this paper we discuss some promising approaches and algorithms for BSS/GCA, especially for ICA and SCA in order to analyze, enhance, perform feature extraction, removing artifacts and denoising of multi-modal, multi-sensory data.

关键词： Independent Component Analysis (ICA) and its extensions Sparse Component Analysis (SCA) sparse representation validity and optimality tests

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