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SPIE conference on Wavelet applications V

作者： Noel, SE Szu, HH Gohel, YJ USN Ctr Surface Warfare Dahlgren Div Dahlgren VA 22448 USA

ISBN: (纸本)081942840X

In this paper we apply the continuous wavelet transform, along with multilayer feedforward neural networks, to the estimation of time-dependent radar doppler frequency. The wavelet transform employs the real-valued Morlet wavelet, which is well matched to the doppler signals of interest. The neural networks are trained with the Levenberg-Marquardt rule, which is much faster than purely gradient-descent learning algorithms such as backpropagation. We also apply Donoho's wavelet denoising with the novel super-Haar wavelet to improve performance for noisy signals. The techniques are applied to the problem of radar proximity fuzing.

关键词： continuous wavelet transform radar signal processing feedforward neural networks wavelet denoising Morlet wavelet super-Haar wavelet

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Multi-scale B-spline snakes for general contour detection

Multi-scale B-spline snakes for general contour detection

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conference on Wavelet applications in signal and image processing VI

作者： Brigger, P Unser, M NIH Bethesda MD 20892 USA

ISBN: (纸本)0819429139

Traditional snakes suffer from slow convergence speed (many control points) and difficult to adjust weighting factors for internal energy terms. We propose an alternative formulation using cubic B-splines, where the knot spacing is variable and controlled by the user. A larger knot spacing allows to reduce the number of parameters, which increases optimization speeds. It also eliminates the need for internal energies, which improves user interactivity. The optimization procedure is embedded into a multi-resolution image representation, where the number of snake-points is adapted to the image grid spacing by correctly adjusting the spline knot spacing. Hence, the proposed method provides a multi-scale approach in both the image and parametric contour domain. Our technique provides fast optimization of the initial snake curve and leads to more stable algorithms in noisy imaging environments. Several biomedical examples of applications are included to illustrate the versatility of the method.

关键词： image segmentation Optimization (mathematics) Brain image enhancement image resolution Mathematical modeling Arteries Biomedical optics Magnetic resonance imaging Ultrasonography

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Dedicated advanced software facility for processing data from earth observing satellites

Dedicated advanced software facility for processing data fro...

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SPIE conference on Earth Observing Systems III

作者： Lampropoulos, GA Boulter, JF AUG Signals Ltd Toronto ON M4V 1K7 Canada

ISBN: (纸本)0819428949

In this paper, a general philosophy about feature windows based applications and a windows-based application are presented for analysis, algorithm development, testing and validation studies for signal, image and Data processing (SIDP) for Space-Based Surveillance (SBS) applications. This dedicated facility is called AUG_SIDP. It performs several specialized tasks such as blur estimation, restoration, CFAR detection, clutter modeling, registration, pixel and data level fusion, target tracking and classification. It is still in the development and testing phase.

关键词： image processing Algorithm development Detection and tracking algorithms Sensors Expectation maximization algorithms image processing algorithms and systems Standards development image segmentation Optical filters Target detection

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Speckle-size metric to improve reconstruction of coherent speckle images

Speckle-size metric to improve reconstruction of coherent sp...

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conference on applications of Digital image processing xxI

作者： Landesman, BT Olson, DF Appl Technol Assoc Albuquerque NM 87106 USA

ISBN: (纸本)0819429155

Robust reconstruction of coherent speckle images from non-imaged laser speckle patterns in the aperture plane of an optical system requires adequate sampling of the speckle intensity at the focal plane. Although detector size cannot be changed dynamically in the course of an experiment to achieve the necessary sampling in every frame, a measure of speckle size could be used to accept or reject individual frames in post-processing software to improve the final reconstructed image. This paper investigates the use of a speckle size metric to gauge the integrity of speckle sampling in each frame of a series of coherent speckle images. Frames containing inadequate sampling are sorted out of the final reconstructed image. The quality of the final recovery for a variety of targets and imaging conditions are compared for sorted and non-sorted reconstructions.

关键词： signal processing speckle phenomena image enhancement autocorrelation reconstruction techniques

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Discriminating a specified digital image from noise process

Discriminating a specified digital image from noise process

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conference on applications of Digital image processing xxI

作者： Nechval, NA Nechval, KN Aviat Univ Riga Dept Appl Math LV-1019 Riga Latvia

ISBN: (纸本)0819429155

In this paper, the problem of discriminating a specified signal from noise process is considered, where the signal is associated with a digital image. Tn the univariate case it is well known that the one-sided t-test is uniformly most powerful for the null hypothesis against all one-sided alternatives. Such a property does not easily extend to the multivariate case. In the present paper, a test is derived for the hypothesis that the mean of a vector random variable is zero against specified alternatives, when the covariance matrix is unknown. This test depends on the given alternatives and is more powerful than Hotelling's T-2. The test is invariant to intensity changes in a background of Gaussian noise and achieves a fixed probability of a false alarm. Thus, operating in accordance to the local noise situation, the test is adaptive. The properties of the proposed test are investigated when a single alternative is specified.

关键词： signal noise process discriminating more powerful test

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Least statistically-dependent basis and its application to image modeling

Least statistically-dependent basis and its application to i...

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conference on Wavelet applications in signal and image processing VI

作者： Saito, N Univ Calif Davis Dept Math Davis CA 95616 USA

ISBN: (纸本)0819429139

Statistical independence is one of the most desirable properties for a coordinate system for representing and modeling images. In reality, however, truly independent coordinates may not exist for a given set of images, or it may be computationally too difficult to obtain such coordinates. Therefore, it makes sense to obtain the least statistically dependent coordinate system efficiently. This basis-we call it Least Statistically-Dependent Basis (LSDB)-can be rapidly computed by minimizing the sum of the differential entropy of each coordinate in the basis library. This criterion is quite different from the Joint Best Basis (JBB) proposed by Wickerhauser. We demonstrate the use of the LSDB for image modeling and compare its performance with JBB and Karhunen-Loeve Basis (KLB).

关键词： statistical independence principal component analysis independent component analysis best basis dimension reduction image modeling

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Wavelet-based embedded zerotree extension to color coding 5

Wavelet-based embedded zerotree extension to color coding

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SPIE conference on Wavelet applications V

作者： Franques, VT USAF Res Lab Munit Directorate Eglin AFB FL 32542 USA

ISBN: (纸本)081942840X

Recently, a new image compression algorithm was developed which employs wavelet transform and a simple binary linear quantization scheme with an embedded coding technique to perform data compaction. This new family of coder, Embedded Zerotree Wavelet (EZW), provides a better compression performance than the current JPEG coding standard for low bit rates. Since The Embedded Zerotree Wavelet coding algorithm emerged, all of the published coding results related to this coding technique are on monochrome images. In this paper the author has enhanced the original coding algorithm to yield a better compression ratio [2], and has extended the wavelet-based zerotree coding to color images. Color imagery is often represented by several components, such as RGB, in which each component is generally processed separately. With color coding, each component could be compressed individually in the same manner as a monochrome image, therefore requiring a threefold increase in processing rime. Most image coding standards employ de-correlated components, such as YlQ or Y, C-B, C-R, and subsampling of the 'chroma' components, such coding technique is employed here. Results of the coding, including reconstructed images and coding performance, will be presented.

关键词： embedded zerotree coding multi-resolution coding color coding image compression wavelets

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A mixed-signal array processor with early vision applications

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IEEE JOURNAL OF SOLID-STATE CIRCUITS 1998年第3期33卷 497-502页

作者： Martin, DA Lee, HS Masaki, I Texas Instruments Inc New Jersey Design Ctr Edison NJ 08837 USA MIT Microsyst Technol Labs Cambridge MA 02139 USA

Many early vision tasks require only 6 to 8 b of precision. For these applications, a special-purpose analog circuit is often a smaller, faster, and lower power solution than a general-purpose digital processor, but the analog chips lack the programmability of digital image processors. This paper presents a programmable mixed-signal array processor which combines the programmability of a digital processor with the small area and low power of an analog circuit. Each processor cell in the array utilizes a digitally programmable analog arithmetic unit with an accuracy of 1.3%. The analog arithmetic unit utilizes a unique circuit that combines a cyclic switched-capacitor analog-to-digital converter (ADC) and digital-to-analog converter (DAC) to perform addition, subtraction, multiplication, and division. Each processor cell, fabricated in a 0.8-mu m triple-metal CMOS process, operates at a speed of 0.8 MIPS, consumes 1.8 mW of power at 5 V, and uses 700 mu m by 270 mu m of silicon area. An array of these processor cells performed an edge detection algorithm and a subpixel resolution algorithm.

关键词： analog processing circuits stereo vision switched capacitor circuits

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image Registration based on complex wavelet pyramid and HVS modeling

Image Registration based on complex wavelet pyramid and HVS ...

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conference on Wavelet applications in signal and image processing VI

作者： Bao, P xu, D Hong Kong Polytech Univ Dept Comp Hong Kong Hong Kong

ISBN: (纸本)0819429139

image Registration, one of the scene encoding approaches, is a very active research topic in computer vision and computer graphics community. This paper presents a robust image registration scheme that employs complex wavelet pyramid and the human visual perceptive thresholding techniques. Complex wavelet transform guarantees not only a global optimal solution, but also the scale and translation invariance for the image alignment. Applying the HVS (Human Visual System) thresholding for wavelet coefficients shows that image can be compressed significantly (30-100:1 ratio) while the detail of the structured information can be retained so that the transformation obtained from the threshholded wavelet images is sufficiently accurate when applying on the original images. The transformation can be progressively refined on the multiresolution decomposition. This guarantees the robustness of the scheme with a better performance than the traditional registration techniques. Moreover, the scheme registers images taken directly by hand-held digital camera without knowing camera motion and any intrinsic parameters of camera.

关键词： image registration complex wavelet HVS IBR image matching

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Block coordinate relaxation methods for nonparametric signal denoising 5

Block coordinate relaxation methods for nonparametric signal...

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SPIE conference on Wavelet applications V

作者： Bruce, AG Sardy, S Tseng, P MathSoft Inc Seattle WA 98109 USA

ISBN: (纸本)081942840X

An important class of nonparametric signal processing methods is to form a set of predictors from ran overcomplete set of basis functions associated with a fast transform (e.g., wavelet packets). In these methods, the number of basis functions can far exceed the number of sample values in the signal, leading to an ill-posed prediction problem. The "Basis Pursuit" de-noising method of Chen, Donoho, and Saunders regularizes the prediction problem by adding an L-1 penalty term on the coefficients for the basis functions. Use of an L-1 penalty instead of L-2 has significant benefits, including higher resolution of signals close in time/frequency and a more parsimonious representation. The L-1 penalty, however, poses a challenging optimization problem that was solved by Chen, Donoho and Saunders using a novel application of interior point methods. In this paper, we investigate an alternative optimization approach based on "Block coordinate relaxation" (BCR) techniques. We show that BCR is globally convergent, and empirically, BCR is faster than interior point methods for a variety of signal de-noising problems.

关键词： signal estimation de-noising nonparametric adaptive wavelets optimization block coordinate relaxation interior point Basis Pursuit Best Basis

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