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A NEW APPROACH TO image-CODING USING 1-D SUBBAND FILTERING 2

引用

CONF ON image processing ALGORITHMS AND TECHNIQUES

作者： YU, TH MITRA, SK Signal and Image Processing Laboratory Department of Electrical and Computer Engineering University of California Santa Barbara 93106 CA United States

ISBN: (纸本)0819405515

Conventional subband coding for image data compression uses two-dimensional (2-D) separable QMF banks in which the analysis and synthesis filters are composed of 1-D filters. Such an implementation produces a large size output image as a result of the convolution process. Various signal extension methods have been proposed to solve this problem. However, these methods have one or more of the following drawbacks: Generation of boundary noise, inability to guarantee aliasing cancellation, and increased computational complexity. In this paper, we present an alternative solution to the problem by converting a 2-D image array to a 1-D array and then using an 1-D QMF bank to process the 1-D signal. In our approach, most of the above drawbacks mentioned above are eliminated. In addition, our approach offers more flexibilities in the type of the filter that can be implementated. © 1991 SPIE. All rights reserved.

关键词： image coding

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New Spectral Canonical Realizations for Time-Varying Linear Systems using a Unified Eigenvalue Concept

New Spectral Canonical Realizations for Time-Varying Linear ...

引用

American Control Conference (ACC)

作者： Jianchao J. Zhu Carroll D. Johnson Electrical and Computer Engineering Department Remote Sensing and Image Processing Louisiana State University Baton Rouge LA USA Electrical and Computer Engineering Department University of Alabama Huntsville AL USA

In this paper, two new spectral canonical relizations are developed for the class of time-varying Scalar Linear Dynamical Systems (SLDS) of the form: y (n) +α n (t)y (n-1) +...+α 2 (t)y+ α 1 (t)y=ß(t)u (n) +ß n (t)u (n-1) +...+ ß 2 (t)u+ß 1 (t)u, and the class of completely controllable time-varying Vector Linear Dynamical Systems (VLDS) of the form: x=A(t)x+b(t)u, y=C(t)x+d(t)u, where A(t), b(t), C(t) and d(t) are, respectively, n×n, n×1, m×n and m×1 matrices; y, x, are vectors of dimension m, n, respectively; and u is a scalar. These new spectral canonical realizations are based on a recently established unified eigenvalue concept, spectral canonical forms and canonical coordinate transformations for matrices over a differential ring. Therefore, they are natural extensions and unifications of the well-known canonical realizations traditionally used for time-invariant SLDS and VLDS using the conventional (time-invariant) eigenvalues. The new results presented here have important applications in the areas of analysis, synthesis, controller design, simulations and implementation for time-varying linear systems.

关键词： Time varying systems Linear systems Eigenvalues and eigenfunctions Vectors Control systems Superluminescent diodes Control system analysis Control system synthesis Analytical models remote sensing

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Active Gravity Gradient Torque Control for Earth-Orbiting Astronomical Telescopes

Active Gravity Gradient Torque Control for Earth-Orbiting As...

引用

American Control Conference (ACC)

作者： A. G. Emslie J. Zhu Department of Physics University of Alabama Huntsville AL USA Electrical and Computer Engineering Department Remote Sensing and Image Processing Laboratory Louisiana State University Baton Rouge LA USA

The controlled pointing of an Earth-orbiting astronomical telescope in the presence of time-dependent gravity-gradient torques is studied using recent techniques for the analysis and synthesis of time-varying linear scalar dynamical systems. We present results which show that effective adaptive control of unstable motions due to gravity gradient torques can be accomplished, resulting in high pointing accuracy and stability for astronomical telescopes in both circular and elliptical orbits.

关键词： Gravity Torque control Telescopes Satellites Earth Motion control Orbits Physics computing remote sensing image processing

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A case study of frozen-time eigenvalues in the stability analysis for periodic linear systems

A case study of frozen-time eigenvalues in the stability ana...

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Southeastern Symposium on System Theory

作者： S. Ray J. Zhu Electrical and Computer Engineering Louisiana State University Baton Rouge LA USA Remote Sensing and Image Processing Laboratory Louisiana State University Baton Rouge LA USA

The stability of linear time-varying systems can be assessed using frozen-time eigenvalues (system eigenvalues computed at each instant). The failure of the sufficiency part of this method was illustrated by L. Markus and M. Yamabe (1960). Their example is examined in a more general setting and in the light of the Floquet characteristic exponent theory which leads to some interesting and enlightening results. These results provide deeper insight into and better understanding of the concept of frozen-time eigenvalues and Floquet characteristic exponents. They are also useful in the robustness analysis for linear time-invariant systems, since the nominal eigenvalues in that case are the frozen-time eigenvalues of the perturbed systems used in such analysis.< >

关键词： computer aided software engineering Eigenvalues and eigenfunctions Stability analysis Linear systems Stability criteria Equations Asymptotic stability remote sensing image processing Laboratories

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A NOVEL NONLINEAR FILTER FOR image-ENHANCEMENT 2

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CONF ON image processing ALGORITHMS AND TECHNIQUES

作者： YU, TH MITRA, SK KAISER, JF Signal and Image Processing Laboratory Department of Electrical and Computer Engineering University of California Santa Barbara 93106 CA United States Bell Communications Research Inc. Room 2A-281 445 South Street Morristown 07962-1910 NJ United States

ISBN: (纸本)0819405515

Recently, a very simple nonlinear algorithm, the so-called Teager's algorithm, has been introduced to calculate the energy of a one-dimensional sequence [1]. In this paper, this algorithm is extended to two-dimensional signals and applied to the contrast enhancement of images. Initial simulation results indicate that the proposed approach yields a superior and visually pleasing enhancement of natural images. The new algorithm is very simple and permits fast implementation. © 1991 SPIE. All rights reserved.

关键词： image enhancement

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A new class of nonlinear filters for image enhancement

A new class of nonlinear filters for image enhancement

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： S.K. Mitra H. Li I.-S. Lin T.-H. Yu Signal and Image Processing Laboratory Department of Electrical and Computer Engineering University of California Santa Barbara CA USA

Two types of very simple two-dimensional nonlinear filters are introduced and applied to image contrast enhancement. The first type is based on a generalization of the Teager's algorithm. A theoretical analysis has shown that this type of nonlinear filter works like a local-mean-weighted highpass filter. Based on this analysis, a second type of nonlinear filter has been developed which works like local-mean-weighted bandpass filter. The proposed image contrast enhancement technique is based on combining the original image with its filtered version obtained using one of the two nonlinear filters. Very high quality enhancement has been achieved for natural images.< >

关键词： Nonlinear filters image enhancement Band pass filters Filtering Signal processing image processing Laboratories Histograms Brightness Pixel

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Automatic neural arbor reconstruction

Automatic neural arbor reconstruction

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： P.M. Gregson Computer Vision and Image Processing Laboratory Department of Electrical Engineering Technical University of Nova Scotia Halifax NS Canada

An algorithm for detecting neural processes in serial optical sections for use in an automated three-dimensional neural reconstruction system is presented. This parsimonious, nonlinear, psychophysically motivated algorithm addresses the problems specific to neural element detection and localization, viz., images with minimal resolution, operators with small spatial supports, highly curved, filamentous features, large variation in feature intensity profile, poor signal-to-noise ratio, and determination of depth without stereo. One first finds the magnitude and orientation of the maximum intensity second directional derivative. A family of curves is locally fitted to these data, and the projections of the data on the curve family are found. If a pixel lies on a curve with sufficient total projection, it is labeled with the magnitude, orientation, curvature, spatial extent, and element displacement. Depth is interpolated from the spatial extent data for corresponding neighborhoods in three adjacent (in depth) images by using an approximation to the depth-dependent optical point spread function. Experimental results using photomicrographs of cat visual cortex are presented.< >

关键词： image reconstruction computer vision Displays Spatial resolution Neural networks Nonlinear optics Optical interconnections Neurons image processing Laboratories

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A path metric for sequential search and its application in edge linking

A path metric for sequential search and its application in e...

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IEEE International Conference on Systems, Man and Cybernetics

作者： A.A. Farag E.J. Delp Engineering Mathematics & Computer Science Department Speed Scientific School University of Louisville Louisville KY USA Computer Vision & Image Processing Laboratory School of Electrical Engineering Purdue University West Lafayette IN USA

The authors develop a path metric for sequential search based on the linear model. The metric forms the heart of an edge-linking algorithm that combines edge elements enhanced by an optimal filter. From a starting node, transitions are made to the goal nodes by a maximum likelihood metric. This metric requires only local calculations on the search space and its use in edge linking provides more accurate results than other linking techniques.< >

关键词： Joining processes image edge detection Filters Application software Heart Layout Decoding Mathematics computer science computer vision

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Real-time high-ratio image compression using adaptive VLSI neuroprocessors

Real-time high-ratio image compression using adaptive VLSI n...

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： B.J. Sheu W.-C. Fang Department of Electrical Engineering Signal and Image Processing Institute University of Southern California Los Angeles CA USA Jet Propulsion Laboratory Advanced Computer Systems and Technology Section California Institute of Technology Pasadena CA USA

An adaptive VLSI neuroprocessor based on vector quantization algorithm has been developed for real-time high-ratio image compression applications. This VLSI neural-network-based vector quantization (NNVQ) module combines a fully parallel vector quantizer with a pipelined codebook generator for a broad area of data compression applications. The NNVQ module is capable of producing good-quality reconstructed data at high compression ratios more than 20. The vector quantizer chip has been designed, fabricated, and tested. It contains 64 inner-product neural units and a high-speed extendable winner-take-all block. This mixed-signal chip occupies a compact silicon area of 4.6*6.8 mm/sup 2/ in a 2.0- mu m scalable CMOS technology. The throughput rate of the 2- mu m NNVQ module is 2 million vectors per second and its equivalent computation power is 3.33 billion connections per second.< >

关键词： image coding Very large scale integration Vector quantization Neural networks Data compression High performance computing Clustering algorithms Application software image reconstruction CMOS technology

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A real-time VLSI neuroprocessor for adaptive image compression based upon frequency-sensitive competitive learning

A real-time VLSI neuroprocessor for adaptive image compressi...

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International Joint Conference on Neural Networks (IJCNN)

作者： W.-C. Fang B.J. Sheu O.T.-C. Chen Jet Propulsion Laboratory Advanced Computer Systems and Technology Section California Institute of Technology Pasadena CA USA Department of Electrical Engineering Signal and Image Processing Institute University of Southern California Los Angeles CA USA

The frequency-sensitive competitive learning (FSCL) algorithm and its associated VLSI neuroprocessor have been developed for adaptive vector quantisation (AVQ). Simulation results show that the FSCL algorithm is capable of producing a good-quality codebook for AVQ at high compression ratios of more than 20 in real time. This VLSI neural-network-based vector quantization design includes a fully parallel vector quantizer and a pipelined codebook generator to provide an effective data compression scheme. It provides a computing capability as high as 3.33 billion connections per second. Its performance can achieve a speedup of 750 compared with SUN-3/60 and a compression ratio of 33 at a signal-to-noise ratio of 23.81 dB.< >

关键词： Very large scale integration image coding Frequency Neural networks Power capacitors Vector quantization CMOS technology image reconstruction Speech coding Data compression

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