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Image compression through fractal surface interpolation and wavelet compression

Image compression through fractal surface interpolation and ...

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Communications, Power and Computing Conference: WESCANEX

作者： R. Dansereau W. Kinsner Department of Electrical and Computer Engineering Signal and Data Compression Laboratory University of Manitoba Winnipeg MAN Canada

The paper presents a perceptual image representation technique based on fractal surface interpolation (FSI), This technique is motivated from the observation that images taken from the real world contain many textures that are self similar, or fractal, in nature. The fractal surface interpolation representation is then compressed using a zero tree wavelet compression subsystem with lossless entropy encoding. The fractal surface interpolation technique described relies on the extraction and reconstruction of self affine fractal surfaces with measured Hurst exponents H*. This gives statistically self similar fractal surfaces used to represent textures in a real world image. Fractional Brownian motion (fBm) through a modified midpoint displacement (MPD) algorithm provides the basis for generating these self affine fractal surfaces between interpolation points.

关键词： Image coding Fractals Surface waves Interpolation Surface reconstruction Surface texture Image representation Entropy Image reconstruction Brownian motion

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An Implementation of ß-Divergence for Blind Source Separation

An Implementation of ß-Divergence for Blind Source Separati...

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Canadian Conference on electrical and computer engineering (CCECE)

作者： N. Gadhok W. Kinsner Signal and Data Compression Laboratory Department of Electrical and Computer Engineering University of Manitoba Winnipeg MAN Canada

Life sustaining biomedical signal processing demands a guarantee that the results produced are accurate and precise. The separation of sources (e.g., demixing two heart signals, one from a mother, and one from a fetus) based only on observations of those mixtures, known as the blind source separation problem, is seen by researchers and scientists as a necessary preprocessing step in order to obtain uncontaminated data for analysis. A method from the field of intelligent signal processing called independent component analysis (ICA) is a promising solution to this problem. However, ICA algorithms and their implementation must be robust to interference, including outliers. Unfortunately, contamination of biomedical recordings by outliers is an unavoidable aspect in signal processing. Mihoko and Eguchi developed an outlier robust ICA algorithm, but code for this algorithm is unavailable. This paper presents a Matlab implementation of their beta-divergence for blind source separation algorithm. The implementation uses a quasi-Newton Broyden-Fletcher-Goldfarb-Shanno (BFGS) optimization, combined with an Armijo conditioned line-search, to minimize the beta-divergence between the density of the source estimates and the product of its hypothesized marginal densities to separate a mixture of statistically independent sources. The implementation is verified by repeating the source separation simulations published by Mihoko and Eguchi. In each simulation the separation results match visually to those published by Mihoko and Eguchi

关键词： Blind source separation signal processing algorithms Independent component analysis Biomedical signal processing Robustness Heart Fetus data analysis signal analysis Interference

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Estimating outlier impact on FastICA using fuzzy inference

Estimating outlier impact on FastICA using fuzzy inference

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Conference of the North American Fuzzy Information Processing Society - NAFIPS

作者： N. Gadhok W. Kinsner Department of Electrical and Computer Engineering Signal and Data Compression Laboratory University of Manitoba Winnipeg MAN Canada

The impact of outliers on signal separation performance of an independent component analysis (ICA) algorithm is an important factor when selecting an ICA algorithm. If an ICA estimator has the property of B-robustness, the influence of an extreme point is bounded, leading to good separation performance in the presence of outliers. Since this property is binary, it does not give the degree of influence an outlier has on the separation performance. To address this issue, a Mamdani-type fuzzy inference, based on the location of a potential outlier and on the skewness of the data set, has been developed. It creates an outlier sensitivity map for an ICA algorithm. The implication of this work is a criterion to switch from one ICA algorithm to another in real time, as determined by the algorithms sensitivity to the data set under consideration. This paper describes estimation of the outlier impact on the separation performance of the non-B-robust FastICA algorithm using a Mamdani-type fuzzy inference. In simulations with data sets contaminated by outliers, the FastICA sensitivity map resembles the separation performance measured by the Amari performance index.

关键词： Independent component analysis signal processing algorithms Inference algorithms Switches Pollution measurement Jitter Higher order statistics Robustness Blind source separation Statistical analysis

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Netlist partitioning for FPGA-based run-time reconfiguration

Netlist partitioning for FPGA-based run-time reconfiguration

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Canadian Conference on electrical and computer engineering (CCECE)

作者： S. Dueck W. Kinsner Department of Electrical and Computer Engineering Signal and Data Compression Laboratory University of Manitoba Winnipeg MAN Canada

This paper demonstrates the feasibility of using automated netlist partitioning to improve the performance of a single FPGA run-time reconfigurable system. Run-time reconfiguration (RTR), an important model for computing, can outperform other computing solutions for some applications and exhibit high architectural flexibility. The performance of RTR is heavily influenced by circuit partitioning. While partitioning procedures to enhance RTR have been previously explored, their nature remains poorly understood. A partitioning system has, therefore, been designed and implemented in software to interface functional circuits to an industry standard graph partitioning heuristic and to study its performance. Experimental results demonstrate that a 103 gate, low-power DCT implementation with 105 nets may be bipartitioned with an interpartition bandwidth of 3 nets.

关键词： Runtime Field programmable gate arrays High performance computing computer applications Application specific integrated circuits Logic programming data compression Laboratories Flexible printed circuits Discrete cosine transforms

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Speech segmentation using multifractal measures and amplification of signal features

Speech segmentation using multifractal measures and amplific...

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IEEE International Conference on Cognitive Informatics

作者： Witold Kinsner Warren Grieder Signal and Data Compression Laboratory Department of Electrical and Computer Engineering University of Manitoba Winnipeg MAN Canada

ISBN: (纸本)9781424425389

This paper describes a fast multiscale time-domain technique for the analysis of natural speech waveforms in the presence of noise. The technique is based on the variance fractal dimension trajectory algorithm that is used not only to detect the external boundaries of an utterance, but also its internal pauses representing the unvoiced speech. The algorithm can also identify internal features of phonemes. The features can be amplified so that the speech utterances can be segmented into sentences, words and phonemes. This approach is superior to other energy-based boundary-detection techniques. These observations are based on extensive experimental results on speech utterances digitized at 44.1 kilosamples per second, with 16 bits in each sample.

关键词： Fractals Trajectory Time series analysis Speech recognition Indexes Time measurement Brownian motion

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Characterizing behaviour of birth/death processes using fractal measures

Characterizing behaviour of birth/death processes using frac...

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Canadian Conference on electrical and computer engineering (CCECE)

作者： J. Greenberg W. Kinsner Department of Electrical and Computer Engineering Signal and Data Compression Laboratory University of Manitoba Winnipeg MAN Canada

The goal of this work was to determine if fractal dimensions would be useful in attempting to characterize and extract emergent behaviour from cellular automata. More specifically, we sought to determine if entropy-based fractal dimensions might prove more useful in extracting behavioural information than morphological dimensions, such as the Hausdorff dimension. This hypothesis was confirmed over several experiments by calculating the gyration dimension, Hausdorff dimension, and by finding Shannon's entropy of the automata's supporting environment during each system iteration.

关键词： Fractals Automata Entropy Lattices Topology data mining Shape Probability Genetics Cloning

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Local and global analysis of multifractal singularity spectrum through wavelets

Local and global analysis of multifractal singularity spectr...

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Canadian Conference on electrical and computer engineering (CCECE)

作者： A. Faghfouri W. Kinsner Department of Electrical and Computer Engineering Signal and Data Compression Laboratory University of Manitoba Winnipeg MAN Canada

This paper presents the implementation aspects pertinent to the computation of the multifractal singularity spectrum through wavelets, and the methods of overcoming them. Multifractals are mixtures of monofractals, and monofractals are self-affine objects that hold power law relationships over several scales. Such multifractals can be detected and measured through a singularity spectrum. Many natural and artificial phenomena such as turbulence, diffusion limited aggregates, and electrical discharges exhibit multifractality. Since these phenomena are highly nonlinear and nonstationary, regular analyses such as Fourier decomposition cannot characterize them effectively. In order to characterize, compare and quantify multifractal objects, appropriate measures such as the Renyi fractal dimension spectrum (RS) and Mandelbrot singularity spectrum (MS) are required. There are two major methods for calculating a singularity spectrum; one is through Legendre transform of the RS, and the other is through the wavelet transform modulus maxima (WTMM) method. This paper provides solutions to the difficulties that arise in the computation of the MS through WTMM, for one-dimensional signals and compares them to the existing multifractal literature and software implementations. Appropriate mother wavelets, continuous wavelet implementation, and thresholding of the wavelet coefficients are also discussed

关键词： Fractals Wavelet analysis Continuous wavelet transforms Wavelet transforms Equations data engineering data compression Laboratories Power engineering computing Aggregates

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A new nonlinear transform for IFS compression of ECG and other signals

A new nonlinear transform for IFS compression of ECG and oth...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： B. Huang W. Kinsner Department of Electrical and Computer Engineering Signal and Data Compression Laboratory University of Manitoba Winnipeg MAN Canada

Presents a nonlinear extension of the affine transform as used in the iterated function systems (IFS) to compress signals and data. Compared with Oien and Narstad's orthogonal transform with compression ratio of 6.0:1 for the electrocardiogram (ECG) signal, the nonlinear approach produces higher compression ratios of 10.2:1, and is more flexible in finding the corresponding strange attractor of the ECG signal. It can model the QRS complex of the ECG signal well, which has been a problem for the affine transform in fractal compression.

关键词： Electrocardiography Fractals data compression Computational complexity Convergence Laboratories Discrete transforms Image coding Image reconstruction Speech

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Modelling multifractal object boundaries using iterated function system

Modelling multifractal object boundaries using iterated func...

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Canadian Conference on electrical and computer engineering (CCECE)

作者： S. Siddiqui A. El-Boustani W. Kinsner Signal and Data Compression Laboratory Department of Electrical and Computer Engineering University of Manitoba Winnipeg MAN Canada

This paper addresses the problem of approximation of arbitrary object boundaries that result from image segmentation. We present a new technique to reconstruct the self-similar boundaries with any fractal or multifractal dimension, using the iterated function system (IFS). The boundaries are assumed to be rough (non-smooth) but crisp (one-pixel wide) and are fractal or multifractal in nature. We show that such boundaries can be regarded as an attractor of a linear IFS having the same multifractal spectrum as the boundaries. We also discuss the hidden variable IFS in order to reconstruct multifractal boundary curvatures, while preserving the original multifractal spectrum of the boundary. Experimental results show that such arbitrary boundaries can be reconstructed more accurately using the IFS as compared to other standard techniques like the midpoint displacement algorithm.

关键词： Fractals Image segmentation Image coding Image reconstruction Video compression Shape Curve fitting data compression Laboratories MPEG 7 Standard

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Multifractal modelling of arbitrary object boundaries in image segmentation

Multifractal modelling of arbitrary object boundaries in ima...

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Canadian Conference on electrical and computer engineering (CCECE)

作者： S. Siddiqui W. Kinsner Signal and Data Compression Laboratory Department of Electrical and Computer Engineering University of Manitoba Winnipeg MAN Canada

This paper addresses the problem of approximation of arbitrary boundaries and edges resulting from image segmentation. Using MPEG-7 terminology, this problem can be considered as the search for a descriptor for a boundary feature of an object. The shape of an object is usually described by its boundaries, to differentiate it from the other regions of the image. Traditionally, Bezier curve fitting has been employed to model the boundaries of objects consisting of smooth and crisp curves. However, natural images contain complex shapes that are difficult to describe by such smooth-boundary modelling techniques. Consequently, we focus on fractals and multifractals to model arbitrary boundaries based on the singularity measure property of fractals. We use wavelets to identify boundary control points and reconstruct the self-similar boundaries with any fractal or multifractal dimension, using the midpoint displacement algorithm.

关键词： Fractals Image segmentation Image coding Shape Curve fitting Video compression MPEG 7 Standard Videoconference Image reconstruction Image storage

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