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Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral imagery XV

作者： Sarkar, Subhadip Healey, Glenn Computer Vision Laboratory Department of Electrical Engineering and Computer Science University of California Irvine Irvine CA 92697 United States

ISBN: (纸本)9780819476005

image synthesis tools provide a means for generating hyperspectral image data without the expense of data collection. An important use of these tools is to provide data for the assessment of image exploitation algorithms. However, the detailed spectral/spatial structure of synthetic images is typically not sufficiently realistic to support the prediction of algorithm performance on real data. In this paper, we develop a new method for hyperspectral texture synthesis that accurately simulates the spectral/spatial structure of real hyperspectral image data. We demonstrate the utility of the new technique by presenting real and synthesized images and by analyzing spectral angle deviation from the mean curves that describe spectral properties. We also demonstrate that a signaturebased detection algorithm has similar performance against real and synthesized hyperspectral backgrounds. © 2009 SPIE.

关键词： Spectroscopy

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Motion-based perceptual quality assessment of video

Motion-based perceptual quality assessment of video

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Human vision and Electronic Imaging XIV

作者： Seshadrinathan, Kalpana Bovik, Alan C. Laboratory for Image and Video Engineering Department of Electrical and Computer Engineering University of Texas at Austin Austin TX United States

There is a great deal of interest in methods to assess the perceptual quality of a video sequence in a full reference framework. Motion plays an important role in human perception of video and videos suffer from several artifacts that have to deal with inaccuracies in the representation of motion in the test video compared to the reference. However, existing algorithms to measure video quality focus primarily on capturing spatial artifacts in the video signal, and are inadequate at modeling motion perception and capturing temporal artifacts in videos. We present an objective, full reference video quality index known as the MOtion-based Video Integrity Evaluation (MOVIE) index that integrates both spatial and temporal aspects of distortion assessment. MOVIE explicitly uses motion information from the reference video and evaluates the quality of the test video along the motion trajectories of the reference video. The performance of MOVIE is evaluated using the VQEG FR-TV Phase I dataset and MOVIE is shown to be competitive with, and even out-perform, existing video quality assessment systems. © 2009 SPIE-IS&T.

关键词： Quality control

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Automatic segmentation of brain structures using geometric moment invariants and artificial neural networks

Automatic segmentation of brain structures using geometric m...

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21st International Conference on Information Processing in Medical Imaging, IPMI 2009

作者： Jabarouti Moghaddam, Mostafa Soltanian-Zadeh, Hamid Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Hospital Detroit MI United States

ISBN: (纸本)3642024971

We propose an automatic method for the segmentation of the brain structures in three dimensional (3D) Magnetic Resonance images (MRI). The proposed method consists of two stages. In the first stage, we represent the shape of the structure using Geometric Moment Invariants (GMIs) in 8 scales. For each scale, an Artificial Neural Network (ANN) is designed to approximate the signed distance function of a desired structure. The GMIs along with the voxel intensities and coordinates are used as the input features of the ANN and the signed distance function as its output. In the second stage, we combine the outputs of the ANNs of the first stage and design another ANN to classify the image voxels into two classes, inside or outside of the structure. We introduce a fast method for moment calculations. The proposed method is applied to the segmentation of caudate, putamen, and thalamus in MRI where it has outperformed other methods in the literature. © 2009 Springer Berlin Heidelberg.

关键词： Neural networks

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A robust method for camera motion estimation in movies based on optical flow

A robust method for camera motion estimation in movies based...

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6th International Conference on Information Technology and Applications, ICITA 2009

作者： Nguyen, Nhat-Tan Laurendeau, Denis Branzan-Albu, Alexandra Computer Vision and Systems Laboratory Department of Electrical and Computer Engineering Laval University Quebec QC G1K7P4 Canada Department of Electrical and Computer Engineering University of Victoria Victoria BC V8W3P6 Canada

ISBN: (纸本)9789810830298

Camera motion estimation plays an important role in digital video analysis algorithms such as video indexing and retrieval or automatic movie analysis. Several algorithms have been proposed to solve this problem in MPEG videos. This paper presents an optical flow based approach for the camera motion estimation in all kinds of digital video formats, especially in movies. It compares the motion vector fields (MVFs) with six predefined templates to determine the type of motion. The MVFs are generated by using high-accuracy optical flow computation. The advantage of the method lies in its robustness to noisy environments such as false motion vectors and object motions. Comprehensive experiments with video clips extracted from well-known feature movies demonstrate the performance of the proposed approach. © ICITA 2009.

关键词： Optical flows

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Mixed projection pursuit-based dimensionality reduction

Mixed projection pursuit-based dimensionality reduction

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Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral imagery XV

作者： Safavi, Haleh Chang, Chein-I Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 United States

ISBN: (纸本)9780819476005

Projection Pursuit (PP) is a component transform technique which seeks a component whose projection vector points to a direction of interestingness in data space which can be specified by a Projection Index (PI). Two most popular component analysis-based techniques, Principal Components analysis (PCA), Independent Component analysis (ICA) can be considered as special cases with their PIs specified by data variance and statistical independency *** the fact that various component analysis-based techniques have been used for Dimensionality Reduction (DR) the components are generally generated by a specific technique. Even in the case of PP, the same PI has been used to generate project components. This paper explores the utility of PP in DR where various projection indexes are used for DR in context of PP. It further lays out a general setting for PP-based DR and develops algorithms to perform one dimension reduction at a time by using different PIs. In order to substantiate our findings, experiments are conducted to demonstrate advantages of the PP with mixed PIs-based DR over traditional PCA-based, ICA-based and PP-based DR techniques.©2009 SPIE.

关键词： Principal component analysis

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Design and analysis of real-time endmember extraction algorithms for hyperspectral imagery

Design and analysis of real-time endmember extraction algori...

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Satellite Data Compression, Communication, and Processing V

作者： Chang, Chein-I Wu, Chao-Cheng Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 United States

ISBN: (纸本)9780819477453

Endmember extraction has recently received considerable attention in hyperspectral data exploitation since they represent crucial and vital information for hyperspectral data analysis. So far, no work has been reported on how to implement endmember extraction algorithms in real-time. An endmember is defined as an idealized signature and may or may not exist as a data sample or an image pixel. The interest of endmember extraction arises in the use of hundreds of contiguous spectral channels that allows a hyperspectral imaging sensor to uncover many subtle substances in diagnostic bands. However, finding such substances also presents a great challenge to hyperspectral data analysts and becomes imperative when it comes to satellite communication if a hyperspectral imaging sensor is operated in space platform where bandwidths used by satellite links may be very limited and downloading all the data may not be realistic in many practical applications. In order to address this need many endmember extraction algorithms have been developed and designed in the past, but no work has been reported on how to implement endmember extraction algorithms in real-time. This paper investigates this issue in designing algorithms for real time processing of endmember extraction and developed several endmember extraction algorithms derived from the widely used N-finder algorithm (NFINDR) that can be implemented in real time. © 2009 SPIE.

关键词： Space platforms

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Soft decision-made hyperspectral measures for target discrimination and classification

Soft decision-made hyperspectral measures for target discrim...

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Imaging Spectrometry XIV

作者： Wu, Chao-Cheng Chang, Chein-I Department of Computer Science and Electrical Engineering Remote Sensing Signal and Image Processing Laboratory University of Maryland Baltimore County Baltimore MD 21250 United States

ISBN: (纸本)9780819477477

Many hyperspectral measures such as Spectral Angle Mapper (SAM), Euclidean Distance (ED), Spectral Information Divergence (SID) calculate values that can be used to measure the closeness between two hyperspectral signatures in terms of spectral similarity. When a hyperspectral measure is used for target discrimination or classification, a commonly used approach assigns a data sample to a spectral signature with the maximum spectral similarity or a class whose mean is most similar to its spectral signature. As a result, such a hyperspectral measure is called a hard decision hyperspectral measure and its performance is evaluated by its confusion matrix. This paper develops a new class of hyperspectral measures, called soft-decision hyperspectral measures which use the similarity value between a data sample and a target signature or a class as an indicator of the likelihood of the data sample assigned to this particular signature or class instead of signature or class map resulting from hard decisions. In order for a soft-decision to perform target discrimination or classification, the soft-decision hyperspectral measure-generated likelihood values are normalized to probabilities so that a threshold can be used to make hard decisions via a recently developed 3D ROC analysis. Experimental study demonstrates that these two approaches yield different results. © 2009 SPIE.

关键词： Classification (of information)

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Progressive dimensionality reduction for hyperspectral imagery

Progressive dimensionality reduction for hyperspectral image...

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Satellite Data Compression, Communication, and Processing V

作者： Safavi, Haleh Liu, Keng-Hao Chang, Chein-I Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 United States

ISBN: (纸本)9780819477453

This paper develops to a new concept, called Progressive Dimensionality Reduction (PDR) which can perform data dimensionality progressive in terms of information preservation. Two procedures can be designed to perform PDR in a forward or backward manner, referred to forward PDR (FPDR) or backward PDR (BPDR) respectively where FPDR starts with a minimum number of spectral-transformed dimensions and increases the spectral-transformed dimension progressively as opposed to BPDR begins with a maximum number of spectral-transformed dimensions and decreases the spectral-transformed dimension progressively. Both procedures are terminated when a stopping rule is satisfied. In order to carry out DR in a progressive manner, DR must be prioritized in accordance with significance of information so that the information after DR can be either increased progressively by FPDR or decreased progressively by BPDR. To accomplish this task, Projection Pursuit (PP)-based DR techniques are further developed where the Projection Index (PI) designed to find a direction of interestingness is used to prioritize directions of Projection Index Components (PICs) so that the DR can be performed by retaining PICs with high priorities via FPDR or BPDR. In the context of PDR, two well-known component analysis techniques, Principal Components analysis (PCA) and Independent Component analysis (ICA) can be considered as its special cases when they are used for DR. © 2009 SPIE.

关键词： Principal component analysis

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Sparse differential connectivity graph of scalp EEG for epileptic patients

Sparse differential connectivity graph of scalp EEG for epil...

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17th European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning, ESANN 2009

作者： Amini, L. Achard, S. Jutten, C. Soltanian-Zadeh, H. Hossein-Zadeh, G.A. David, O. Vercueil, L. INPG Domaine universitaire- BP 46 F-38402 Grenoble Cedex France Electrical and Computer Engineering Department University of Tehran Tehran Iran Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI 48202 United States U836 38043 Grenoble France

ISBN: (纸本)2930307099

The aim of the work is to integrate the information modulation of the inter-relations between EEG scalp measurements of two brain states in a connectivity graph. We present a sparse differential connectivity graph (SDCG) to distinguish the effectively modulated connections between epileptiform and non-epileptiform states of the brain from all the common connections created by noise, artifact, unwanted background activities and their related volume conduction effect. The proposed method is applied on real epileptic EEG data. Clustering the extracted features from SDCG may present valuable information about the epileptiform focus and their relations.

关键词： Brain

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Spectral derivative feature coding for hyperspectral signature analysis

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Pattern Recognition 2009年第3期42卷 395-408页

作者： Chang, Chein-I Chakravarty, Sumit Chen, Hsian-Min Ouyang, Yen-Chieh Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 United States Department of Electrical Engineering National Chung Hsing University Taichung Taiwan Environmental Restoration and Disaster Reduction Research Center National Chung Hsing University Taichung Taiwan Department of Medical Research China Medical University Hospital Taichung Taiwan Department of Radiology China Medical University Hospital Taichung Taiwan

This paper presents a new approach to hyperspectral signature analysis, called spectral derivative feature coding (SDFC). It is derived from texture features used in texture classification to dictate gradient changes among adjacent bands in characterizing spectral variations so as to improve better spectral discrimination and classification. In order to evaluate its performance, two known binary coding methods, spectral analysis manager (SPAM) and spectral feature-based binary coding (SFBC) are used to conduct comparative analysis. Experimental results demonstrate that the proposed SDFC performs more effectively in capturing spectral characteristics than do SPAM and SFBC. © 2008 Elsevier Ltd. All rights reserved.

关键词： Spectrum analysis

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