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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Chein-I Chang Shao-Shan Chiang Qian Du Hsuan Ren A. Ifarragaerri Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD USA Department of Computer Science and Electrical Engineering Texas A and M University Kingsville TX USA Biological and Chemical Command US Army MD USA

ROC (Receiver Operating Characteristic) analysis has been widely used to evaluate detection performance. It is based on the Neyman-Pearson detection theory, which solves binary hypothesis testing problems. In mixed pixel classification many algorithms that are developed to estimate abundance fractions (of image endmembers) generally produce gray scale images. As a result, they are not directly applied to hypothesis testing problems. Instead of using the standard ROC curve generated by the detection power versus the false alarm probability, a 3-dimensional (3D) ROC curve is developed in this paper for subpixel detection. It is a 3D plot derived from the mean-detection probability versus the mean-false alarm rate with the third dimension specified by abundance fractions produced by subpixel detection algorithms. In order to illustrate the utility of the proposed 3D ROC analysis in subpixel detection, several linear unmixing-based algorithms are used for performance evaluation.

关键词： Testing Pixel Performance analysis computer science Chemical analysis image segmentation Signal processing image processing Laboratories Chemical processes

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Color image-based angular map-driven snakes

Color image-based angular map-driven snakes

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IEEE International Conference on image processing

作者： A. Dumitras A.N. Venetsanopoulos Speech and Image Processing Services Research Laboratory AT and T Research Laboratories Middletown NJ USA The Edward Rogers Sr. Department of Electrical and Computer Engineering University of Toronto Toronto ONT Canada

We propose a method for shape description of objects in color images. Our method employs angular maps to identify significant changes of color within the image, which are then used to drive snake models. Experimental results show that our angular map-driven snake method not only yields an accurate description of an object shape, but also it is computationally efficient.

关键词： Color Shape image edge detection Laplace equations Laboratories Speech processing image processing USA Councils image retrieval Animation

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Multimodality image registration and fusion using neural network

Multimodality image registration and fusion using neural net...

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3rd International Conference on Information Fusion, FUSION 2000

作者： Mostafa, Mostafa G. Farag, Aly A. Essock, Edward Computer Vision and Image Processing Laboratory Department of Electrical and Computer Engineering University of Louisville Louisville KY 40292 United States Department of Psychology University of Louisville Louisville KY 40292 United States

ISBN: (纸本)2725700000

Multi-modality image registration and fusion are essential steps in building 3D models from remote sensing data. In this paper, we present a neural network technique for the registration and fusion of multi-modality remote sensing data for the reconstruction of 3D models of terrain regions. A feedforward neural network is used to fuse the intensity data sets with the spatial data set after learning its geometry. Results on real data are presented. Human performance evaluation is assessed on several perceptual tests in order to evaluate the fusion results. © 2000 Int. Soc. Inf. Fusion.

关键词： image fusion

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A method for restoration of low-resolution document images

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International Journal on Document Analysis and Recognition 2000年第4期2卷 200-210页

作者： Thouin, Paul D. Chang, Chein-I Department of Defense Fort Meade MD 20755 United States Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County 1000 Hilltop Circle Baltimore MD 21250 United States

image restoration using resolution expansion is important in many areas of image processing. This paper introduces a restoration method for low-resolution text images which produces expanded images with improved definition. This technique creates a strongly bimodal image with smooth regions in both the foreground and background, while allowing for sharp discontinuities at the edges. The restored image, which is constrained by the given low-resolution image, is generated by iteratively solving a nonlinear optimization problem. Low-resolution text images restored using this technique are shown to be both quantitatively and qualitatively superior to images expanded using the standard methods of linear interpolation and cubic spline expansion. Experimental results demonstrate that text images created by this new algorithm improve optical character recognition accuracy more than images obtained by existing expansion methods. © 2000 Springer-Verlag Berlin Heidelberg.

关键词： Restoration

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Multimodality image registration and fusion using neural network

Multimodality image registration and fusion using neural net...

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International Conference on Information Fusion

作者： M.G. Mostafa A.A. Farag E. Essock Department of Electrical and Computer Engineering Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Department of Psychology University of Louisville Louisville KY USA

关键词： image registration Neural networks Hyperspectral sensors Remote sensing image reconstruction Geometry Remote monitoring Intelligent sensors Satellites Laser radar

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An adaptive deterministic annealing approach for medical image segmentation

An adaptive deterministic annealing approach for medical ima...

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Conference of the North American Fuzzy Information processing Society - NAFIPS

作者： S. Mitra R. Castellanos S. Joshi Computer Vision and Image Analysis Laboratory Department of Electrical and Computer Engineering Texas Tech University Lubbock TX USA

We present a stochastic model based technique that uses the concept of deterministic annealing to obtain a generalized solution to the nonconvex optimization problem encountered by many image segmentation techniques. Deterministic annealing [DA] is an elegant and useful tool for clustering and classification. This novel optimization approach works with the efficiency of a deterministic procedure and has been successfully applied to a number of combinatorial optimization problems. We demonstrate effective segmentation of simulated MR brain images and provide a quality measure for accuracy of classification. A generalized deterministic annealing procedure, which works tender a structural constraint of mass or density, has been utilized for this purpose. This method produces a hierarchy of solutions giving segmentation results from a coarse to a fine level. Automatic edge detection can be performed using these solutions that are at different degrees of coarseness. The procedure has been made more efficient by utilizing a new similarity parameter from the concepts of neuro-fuzzy clustering.

关键词： Annealing Biomedical imaging image segmentation Brain modeling Clustering algorithms image edge detection Lagrangian functions computer vision Laboratories Stochastic processes

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Multimedia security: Does signal processing have a place in securing the digital world?

Multimedia security: Does signal processing have a place in ...

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European Signal processing Conference (EUSIPCO)

作者： Edward J. Delp Video and Image Processing Laboratory School of Electrical and Computer Engineering Purdue University West Lafayette Indiana

With the recent growth of networked multimedia systems, techniques are needed to prevent (or at least deter) the illegal copying, forgery and distribution of digital media elements such as audio, images and video. The problem is that a copy of a media element is identical to the original. It is also desirable to determine where and by how much a multimedia element has been changed from the original. One classical approach to the problem of protecting "digital content" has been the use of cryptographic methods such as encryption and authentication. Recently other methods have been proposed to improve one's claim of ownership over a digital media element by inserting a small amount of distortion directly into the media element. This distortion, known as a digital watermark, can be used to uniquely identify the owner of the content. Digital watermarking research is mainly the domain of the signal processing community that is very naive when considering real world security problems. Also the attitude of the academic community that it has the "right" to copy and reproduce any multimedia element is curious at best and perhaps conveys the wrong message to our students. The use of the "Lena" image is a good example of this. In this talk I will survey the current state of multimedia security and describe important research issues. I will also express some concern that perhaps we in the signal processing community might want to understand the "security scenario" before making grandiose claims about how our latest watermarking technique will save the world!

关键词： Multimedia communication Media Signal processing Watermarking Communities Streaming media

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A rate-distortion approach to wavelet-based encoding of predictive error frames

A rate-distortion approach to wavelet-based encoding of pred...

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IEEE International Conference on image processing

作者： E. Asbun P. Salama E.J. Delp Video and Image Processing Laboratory School of Electrical and Computer Engineering Purdue University West Lafayette IN USA Department of Electrical and Computer Engineering Purdue School of Engineering and Technology Indiana University-Purdue University Indianapolis Indianapolis IN USA

We develop a framework for efficiently encoding predictive error frames (PEF) as part of a rate scalable, wavelet-based video compression algorithm. We investigate the use of rate-distortion analysis to determine the significance of coefficients in the wavelet decomposition. Based on this analysis, we allocate the bit budget assigned to a PEF to the coefficients that yield the largest reduction in distortion, while maintaining the embedded and rate scalable properties of our video compression algorithm.

关键词： Rate-distortion Encoding image coding Video compression computer errors Redundancy Wavelet analysis Decoding Scalability Transform coding

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Unsupervised seed determination for a region-based color image segmentation scheme

Unsupervised seed determination for a region-based color ima...

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IEEE International Conference on image processing

作者： N. Ikonomakis K.N. Pataniotis A.N. Venetsanopoulos Department of Electrical and Computer Engineering Digital Signal & Image Processing Laboratory University of Toronto Toronto ONT Canada University of Toronto Toronto ON CA

ISBN: (纸本)0780362977

A color image segmentation technique is presented for use in coding and/or compression of video-conferencing sequences. The proposed technique utilizes the perceptual HSI (hue, saturation, intensity) color space and incorporates an unsupervised seed determination algorithm that finds the seed pixels that are in the spatial center of the regions in the image. The algorithm employs a hierarchy system where seeds found at the highest level produce the best results. The region growing algorithm uses these seeds to grow regions by appending to each seed pixel those neighboring pixels that satisfy a certain homogeneity criterion. The technique is found to be robust and relatively computationally inexpensive. The effectiveness of the algorithm is found to be much improved over techniques used in the past.

关键词： Color image segmentation Pixel image coding image converters Signal processing image processing Laboratories Robustness Partitioning algorithms

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Unsupervised fully constrained squares linear spectral mixture analysis method for multispectral imagery

Unsupervised fully constrained squares linear spectral mixtu...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： D.C. Heinz Chein-I Chang Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD USA

Subpixel detection and quantification of materials in multispectral imagery presents a challenging problem due to a relatively low number of spectral bands available for analysis in which case the number of spectral bands may be less than the number of materials to be detected and quantified. The problem is even more difficult when the image scene is unknown and no prior knowledge is available. Under this circumstance, the desired information must be obtained directly from the image data. The authors present an unsupervised least squares-based linear mixture analysis method coupled with a band expansion technique for multispectral image analysis. This method allows the authors to extract necessary endmember information from an unknown image scene so that the endmembers present in the image can be detected and quantified. The band expansion technique creates additional bands from the existing multispectral bands using band-to-band nonlinear correlation. These expanded bands ease the problem of insufficient bands in multispectral imagery and can improve and enhance the performance of the proposed method. The experimental results demonstrate the advantages of the proposed approach.

关键词： Least squares methods Spectral analysis Multispectral imaging Layout image analysis Vectors Hyperspectral sensors Hyperspectral imaging Pixel Least squares approximation

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