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Maximum likelihood approach to image texture and acoustic signal classification

iee PROCEEDINGS-vision image AND SIGNAL processing 1999年第1期146卷 34-39页

作者： Thyagarajan, KS Nguyen, T Persons, CE San Diego State Univ Dept Elect & Comp Engn San Diego CA 92182 USA RDTE NCCOSC San Diego CA 92152 USA

The authors describe a method of classifying natural textures based on the maximum likelihood parameter estimation technique. The novelty of the technique lies in the use of textural features that are derived from the subbands of a wavelet transformed image via the co-occurrence matrices. A maximum likelihood classifier is designed using a set of training texture samples. Ten different Brodotz textures have been classified using this procedure with an average classification accuracy of 99.7%. The main emphasis is to apply this technique to the classification of underwater acoustic signals. A time-frequency plot is obtained for each segment of the acoustic signal and then converted to an intensity pattern. The textural classification scheme is then applied to the intensity patterns of the acoustic signals. Eight different underwater acoustic signals have been classified by this procedure with an average accuracy of 99.99%.

关键词： Sonar and acoustic radar image classification Acoustic signal processing Simulation, modelling and identification maximum likelihood estimation transform coding acoustic signal processing average accuracy time-frequency plot intensity patterns maximum likelihood parameter estimation co-occurrence matrices training texture samples image representation image resolution computer vision and image processing techniques Brodotz textures multiresolution representation acoustic signal classification image coding underwater sound average classification accuracy subbands Integral transforms in numerical analysis Underwater sound textural features image texture image and video coding wavelet transformed image underwater acoustic signals image texture classification wavelet transforms maximum likelihood classifier wavelet transform

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iee Electronics Division colloquium on multiresolution modelling and analysis in image processing and computer vision

IEE Electronics Division Colloquium on Multiresolution Model...

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Proceedings of the 11th Biennial University/Government/Industry Microelectronics Symposium

The proceedings contains 11 papers from the iee colloquium on multiresolution modelling and analysis in image processing and computer vision on April 21, 1995 at the Savoy Place, London, UK. Topics discussed include i... 详细信息

关键词： image processing

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multiresolution stochastic image models

Multiresolution stochastic image models

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iee colloquium on multiresolution modelling and analysis in image processing and computer vision

作者： R. Wilson S.C. Clippingdale Computer Science Department University of Warwick Coventry UK

The paper examines multiresolution image models, illustrating the main classes of models and how they can be used in the development of image processing algorithms, from data compression and enhancement to low-level v... 详细信息

关键词： Machine vision Data compression image enhancement image processing Stochastic processes

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multiresolution image registration

Multiresolution image registration

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iee colloquium on multiresolution modelling and analysis in image processing and computer vision

作者： P. Kent Image Process. & Interpretation Group DRA Malvern UK

The work describes how the application of multiresolution techniques improves the performance of an image registration algorithm. The algorithm determines the parameter values of a global geometric transformation that corrects gross misregistration between two images. It is assumed that the only distortion present is geometric and that there is no systematic radiometric distortion, i.e. any differences in intensity are due to noise, and not to overall brightness or contrast differences. The method is based upon that of Dana and Anandan (1993), who use a similar technique to register binary edge images for multi-modal registration.

关键词： image registration

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Improvements in MRF parameter estimation

Improvements in MRF parameter estimation

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iee colloquium on multiresolution modelling and analysis in image processing and computer vision

作者： B. Calder L. Linnett S. Clarke D. Carmichael Department of Computing and Electrical Engineering Heriot-Watt University Edinburgh UK DRA Maritime Division Weymouth Dorset UK

We describe a new perspective on a method of parameter estimation first proposed by Derin and Elliot (1987) and extended by Gurelli and Onural (1994) which we believe to be useful in fast estimation of Markov random field parameters. We also present a case for using binary Markov random fields for image analysis by linking them with a spatial greyplane analysis technique.

关键词： image processing Markov processes Parameter estimation Stochastic processes

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A multiresolution block matching technique for image motion estimation

A multiresolution block matching technique for image motion ...

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iee colloquium on multiresolution modelling and analysis in image processing and computer vision

作者： I. Rhee G.R. Martin R.A. Packwood Department of Computer Science University of Warwick Coventry UK

To better utilise the information in the high-resolution small-blocks of an image it is necessary to generate accurate estimates of the motion. We present a bottom-up multiresolution block matching technique. We first compute a set of candidate motion vectors for each comparatively small block. We then take an intersection of these sets of neighbouring blocks. The resulting set is the set of candidate motion vectors for the larger block that encompasses the neighbouring blocks. This way, it preserves the motion information extracted at high resolution and uses the information at low resolutions only selectively to improve the motion estimates.

关键词： image matching Motion analysis Vectors

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multiresolution morphological fusion of MR and CT images of the human brain

Multiresolution morphological fusion of MR and CT images of ...

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iee colloquium on multiresolution modelling and analysis in image processing and computer vision

作者： S. Marshall G. Matsopoulos J. Brunt Department of Electronic and Electrical Eng University of Strathclyde Glasgow UK Department of Medical Physics Clatterbridge Centre for Oncology Wirral Merseyside UK

This paper compares two types of multiresolution data structure for data fusion, the data pyramid and the data cylinder. Data pyramids are well established, and in recent years nonlinear operators such as alternating sequential morphological filters have been used in their construction. The essential difference between pyramids and cylinders is that pyramids undergo subsampling at each level. This paper compares the fusion of medical images through pyramids and cylinders and also considers the effects of different sampling ratios.

关键词： Brain Tomography image coding Biomedical image processing Magnetic resonance imaging Multisensor systems

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Estimating disparity and motion using multiresolution Fourier analysis

Estimating disparity and motion using multiresolution Fourie...

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iee colloquium on multiresolution modelling and analysis in image processing and computer vision

作者： A.D. Calway S.A. Kruger Dept. of Comput. Math. Univ. of Wales Coll. of Cardiff UK

The paper describes a multiresolution approach to tackling the image registration problem-the identification of corresponding points or regions in two or more images of a scene derived, for example, from different viewpoints or at different times. It is a region-based approach in which disparity estimates obtained from local correlations computed via the frequency domain are incorporated within a multiresolution search procedure. As such the approach removes the link between frequency content and disparity, while retaining the efficiency of multiresolution searching. The scheme is implemented within the framework of a generalised wavelet transform, the multiresolution Fourier transform, which also provides the potential for the incorporation of more complex matching criteria based on feature information and affine transformation. The aim is to outline the main components of the basic algorithm and present results of its use in estimating the disparity between binocular views of a scene and in estimating motion from video sequences.

关键词： Fourier transforms image matching image registration image segmentation image sequence analysis Motion analysis Wavelet transforms

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Coarsening rules for regularization parameters in multiresolution approaches

Coarsening rules for regularization parameters in multiresol...

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iee colloquium on multiresolution modelling and analysis in image processing and computer vision

作者： P. Baikas D. Levett M. Petrou Dept. of Electron. & Electr. Eng. Surrey Univ. Guildford UK

We present results concerning the coarsening of model parameters which are independent of the position in the image. We argue that these parameters can be seen in one of two ways: either as the regularisation parameters which effectively control the amount of smoothing imposed to the data, or as the Markov random field parameters which, for example, describe the model of the underlying texture that is being restored by the optimization process. We review results derived by Szeliski (1989) which are concerned with the regularization case and describe experiments which check these results. We examine the case when the model parameters are not only regularization parameters, but also attempt to model a (possibly) intricate texture pattern.

关键词： image representations image restoration image texture analysis Markov processes Optimization methods Stochastic processes Smoothing methods

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Fast multi-resolution image processing for PCB manufacture

Fast multi-resolution image processing for PCB manufacture

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iee colloquium on multiresolution modelling and analysis in image processing and computer vision

作者： S.E. Hodges R.J. Richards Department of Engineering University of Cambridge

This paper addresses the problem of locating visual features on a printed circuit board (PCB) to facilitate automated manufacture and assembly of PCBs. A brief introduction to PCB manufacture is given to provide background information and demonstrate the large variation in types of PCB. An overview of visual servoing explains why the features must be located quickly and robustly. By presenting an algorithm which is able to locate features in the image of a PCB at any given scale quickly and then determine their position accurately, this paper aims to satisfy the criteria outlined. Following a discussion of the approach taken to detect features in the image, the theory behind a particularly efficient implementation is presented. Based on an approach to range searching in computational geometry, partial summation eliminates much of the processing which would otherwise be involved. It is particularly suited to multi-resolution image processing, and can be used both to find candidate feature locations and to confirm their precise position. Results which demonstrate the power of the technique for processing PCB images are given, and extensions to other applications are considered.

关键词： Computational geometry image processing Printed circuit fabrication Surface mounting

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