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ieee symposium on Nuclear Science (NSS/MIC)

作者： W.Y. Sun S.E. Derenzo T.F. Budinger Department of Electrical Engineering and Computer Sciences Lawrence Berkeley Laboratory University of California Berkeley CA USA

An adaptive Wiener filter has been developed for the convolution backprojection (CBP) reconstruction of positron emission tomograph (PET) images. An approach is proposed for applying minimum mean square error (MMSE) producing filters in the image space by estimating the power spectra of the signal and noise in the reprojections of the reconstructed images. Backprojection-algorithm-dependent colorization of the white input noise process and angle-dependent signal are accounted for in the proposed algorithm to compute the Wiener filter. Reconstruction results using the proposed algorithm are compared with the manually selected Butterworth-type filters on data obtained with the Donner 600-crystal tomograph. Simulation results using the uniform circular disk phantom of estimating the noise and signal power spectra in the reconstructed images produced reasonable estimates of the Wiener filter.< >

关键词： Wiener filter Positron emission tomography image reconstruction Convolution Radioactive decay Mean square error methods White noise Colored noise signal processing computational modeling

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Tomographic reconstruction using optoelectronic architecture

Tomographic reconstruction using optoelectronic architecture

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ieee International symposium on Circuits and Systems (ISCAS)

作者： T. Lu S.S. Udpa L. Udpa Department of Electrical Engineering & Computer Engineering Iowa State University Iowa IA USA

A novel approach for implementing tomographic reconstruction algorithms using optoelectronic CCD (charge coupled device) structures is described. The approach employs the algebraic reconstruction technique (ART). The proposed method overcomes the problems of poor reconstruction results and implementation difficulties traditionally associated with ART. The optoelectronic approach described offers significant advantages over existing electronic methods both in terms of computational speed and quality of reconstruction.< >

关键词： Tomography image reconstruction Subspace constraints Computer architecture Reconstruction algorithms Charge coupled devices Optical signal processing Optical devices Pixel Equations

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COASTLINE DETECTION AND TRACING IN SAR imageS

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ieee TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 1990年第4期28卷 662-668页

作者： LEE, JS Center for Advanced Space Sensing Naval Research Laboratory Inc. Washington D.C. DC USA

images of coastlines generated by Synthetic Aperture Radars (SAR’s) suffer from a number of deficiencies which arise from the presence of the speckle effect and the strong signal return from a wind-roughened, wave-modulated sea. The frequent lack of contrast caused by these effects makes coastline detection difficult by most conventional procedures such as gray-level thresholding or segmentation by edge magnitude. This paper describes an algorithm for the global detection of coastlines based on a sequence of basic image-processing procedures and a new edge tracing algorithm. The application of the proposed procedure to Seasat SAR and SIR-B (Shuttle imaging Radar B) images demonstrates that with only a modest computational burden it produces a good visual match between the detected coastline and the coastline of original image. Additionally, the separation of land from water achieved by this algorithm permits clean pseudocoloring of coastal area images. © 1990 ieee

关键词： Speckle Filters image edge detection Noise level Sea measurements Impedance Humans Government Protection Histograms

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A FREQUENCY-DOMAIN ALGORITHM FOR MULTIFRAME DETECTION AND ESTIMATION OF DIM TARGETS

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ieee TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE intelligence 1990年第4期12卷 398-401页

作者： PORAT, B FRIEDLANDER, B SIGNAL PROC TECHNOL LTD PALO ALTOCA 94303

An algorithm for detecting moving targets by imaging sensors and estimating their trajectories is proposed. The algorithm is based on directional filtering in the frequency domain, using a bank of filters for all possible target directions. The directional filtering effectively integrates the target signal, resulting in an improved signal-to-noise ratio. Working in the frequency domain facilitates a considerable reduction in computational requirements compared to time-domain algorithms. The algorithm is described in detail, and its false alarm and detection probabilities are analyzed.

关键词： Frequency domain analysis Frequency estimation signal processing algorithms Trajectory signal to noise ratio image sensors Filtering algorithms Target tracking Optical filters Filter bank INSPEC: Controlled Indexing tracking systems computerised picture processing fast Fourier transforms filtering and prediction theory INSPEC: Non-Controlled Indexing detection probabilities fast Fourier transforms computerised picture processing multiframe estimation trajectories estimation frequency domain algorithm multiframe detection dim targets moving targets imaging sensors directional filtering

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SCALE-SPACE FOR DISCRETE signalS

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ieee TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE intelligence 1990年第3期12卷 234-254页

作者： LINDEBERG, T Comput. Vision & Associative Pattern Process. Lab. R. Inst. of Technol. Stockholm Sweden

A basic and extensive treatment of discrete aspects of the scale-space theory is presented. A genuinely discrete scale-space theory is developed and its connection to the continuous scale-space theory is explained. Special attention is given to discretization effects, which occur when results from the continuous scale-space theory are to be implemented computationally. The 1D problem is solved completely in an axiomatic manner. For the 2D problem, the author discusses how the 2D discrete scale space should be constructed. The main results are as follows: the proper way to apply the scale-space theory to discrete signals and discrete images is by discretization of the diffusion equation, not the convolution integral; the discrete scale space obtained in this way can be described by convolution with the kernel, which is the discrete analog of the Gaussian kernel, a scale-space implementation based on the sampled Gaussian kernel might lead to undesirable effects and computational problems, especially at fine levels of scale; the 1D discrete smoothing transformations can be characterized exactly and a complete catalogue is given; all finite support 1D discrete smoothing transformations arise from repeated averaging over two adjacent elements (the limit case of such an averaging process is described); and the symmetric 1D discrete smoothing kernels are nonnegative and unimodal, in both the spatial and the frequency domain.

关键词： signal resolution Kernel Smoothing methods Convolution image resolution Laplace equations Filtering signal processing Computer vision INSPEC: Controlled Indexing signal processing discrete systems INSPEC: Non-Controlled Indexing frequency domain signal processing nonnegative kernels unimodal kernels spatial domain discrete signals discrete scale-space theory diffusion equation Gaussian kernel discrete smoothing transformations

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A Comparison Of Legendre and Walsh Moments

A Comparison Of Legendre and Walsh Moments

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Southern African Conference on Communications and signal processing (COMSIG)

作者： A.L. Nel Laboratory for Cybernetics Rand Afrikaans University

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DSP architectural features for intelligence and control applications

DSP architectural features for intelligence and control appl...

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ieee International symposium on Intelligent Control (ISIC)

作者： I. Radivojevic J. Herath ECE Department Drexel University Philadelphia PA USA

The architectural features of digital signal processors (DSPs) that make them applicable to intelligent control are discussed. The impact of on-chip parallel features on numeric processing capabilities and efficient program execution is described. I/O and real-time features of DSPs are examined. The role of numerical computations in preprocessing vocal, visual and written input data in real-time AI systems is considered. The parallels between neural and DSP computations are illustrated. A node configuration for a virtually implemented neural network, based on a commercially available DSP chip, is proposed.< >

关键词： Digital signal processing Intelligent control Digital signal processing chips Hardware Arithmetic Filtering computational intelligence Digital signal processors Parallel processing Instruction sets

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Efficient 2-D analysis/synthesis filter banks for directional image component representation

Efficient 2-D analysis/synthesis filter banks for directiona...

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ieee International symposium on Circuits and Systems (ISCAS)

作者： R.H. Bamberger M.J.T. Smith Digital Signal Processing Laboratory School of Electrical Engineering Georgia Institute of Technology Atlanta GA USA

A filter bank for the directional decomposition of images is described. The filter bank represents a union of two powerful image processing tools: directional decomposition and subband decomposition. The directional components correspond to wedge-shaped regions in the frequency spectrum. The filter bank is implemented in a tree structure where each two-band system is maximally decimated and provides either exact or aliasing free reconstruction. The design of the analysis/synthesis filter is such that the filter bank can be implemented in an extremely efficient computational form. The design method described uses conventional 1-D analysis/synthesis filters as prototypes and thereby circumvents designing 2-D filters.< >

关键词： image analysis Channel bank filters Filter bank signal synthesis signal analysis image processing Frequency image reconstruction Design methodology signal design

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Analog signal processing using cellular neural networks

Analog signal processing using cellular neural networks

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ieee International symposium on Circuits and Systems (ISCAS)

作者： K.R. Krieg L.O. Chua L. Yang Department of Electrical Engineering and Computer Sciences University of California Berkeley CA USA

The cellular neural network (CNN) is an example of very-large-scale analog processing or collective analog computation. The CNN architecture combines some features of fully connected analog neural networks with the nearest-neighbor interactions found in cellular automata. These networks have numerous advantages both for simulation and for VLSI implementation and can perform (though are not limited to) several important image processing functions. The important features which enable the CNN architecture to perform signal processing functions using standard VLSI technology are discussed. Circuit characteristics are outlined, and examples of cellular neural network signal processing are presented. Connected segment extraction is illustrated by examples, as is histogramming using a two-layer CNN.< >

关键词： signal processing Cellular neural networks Very large scale integration Analog computers Computer networks Computer architecture Neural networks computational modeling Circuit simulation image processing

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Time-frequency estimation from either signal domain-implementation on a RISC system

Time-frequency estimation from either signal domain-implemen...

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ieee International symposium on Circuits and Systems (ISCAS)

作者： D.O. Adams J. Wilbur Power Network Scrvices NCR Corporation West Columbia USA Signal and Image Processing Branch Naval Coastal Systems Center Panama FL USA

A Wigner-distribution-based spectral estimation is optimized for high-level-language implementation on a reduced-instruction-set-computer (RISC) architecture. Traditionally, time-frequency estimators have relied on time histories for the input. The implementation presented allows for equivalent transformation to the t-w plane given either time or frequency input data. The estimator employs a generalized form of the WD and is developed at the algorithm level to offer both flexibility and computational efficiency. Several DFT alternatives including the radix-2 FFT, radix-4 FFT, SRFFT, WFTA, and PFA are investigated in terms of relative computational delays versus a floating-point addition-time-to-multiply-time ratio.< >

关键词： Time frequency analysis Reduced instruction set computing Clocks Smoothing methods High level languages History signal processing algorithms Discrete Fourier transforms signal processing Workstations

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