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PURSUIT: an automatic classification tool for remote sensing data

PURSUIT: an automatic classification tool for remote sensing...

引用

IEEE International Symposium on Geoscience and remote sensing (IGARSS)

作者： T.M. Bachmann M.H. Bettenhausen Remote Sensing Division Code 7212 Naval Research Laboratory Inc. Washington D.C. DC USA IMSI Inc. Arlington VA USA

PURSUIT (Projection Understanding and recognition from a SUite of intelligent Tools) has been under development at the Naval Research Laboratory for a number of years. It is a versatile software tool designed to address the problem of automatic feature extraction and classification from remote sensing data. Although the tool can be applied to a variety of applications outside of the field of remote sensing, it is particularly useful for automated remote sensing imagery analysis. To date, the package has been applied to imagery from a variety of different sensor types including: multispectral, hyperspectral, synthetic aperture radar (SAR), and multi-sensor data. Because of its modular design, PURSUIT is re-configurable and the suite of algorithms that comprise it can be flexibly combined to address new applications as they arise. As such, new algorithms can be easily added. Algorithms included in the present corpus consist of a variety of in-house algorithms, as well as standard algorithms derived from many areas of the statistical pattern recognition literature, including adaptive vector quantization, unsupervised and supervised feature extraction and classification, and neural networks. Each module contains a number of different preprocessing and post-processing options, and the input data may be spectral, spatial, or spatial-spectral. The modular design of the package allows data from multiple sources to be combined in the same overall automatic classification model.

关键词： remote sensing Feature extraction Packaging Hyperspectral sensors Laboratories Software tools Software design Application software image analysis image sensors

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Experiments in transform-based range image compression

Experiments in transform-based range image compression

引用

International conference on pattern recognition

作者： R.J. Campbell P.J. Flynn Sharp Laboratories of America Camas WA USA CS&E Dept University of Notre Dame IN USA

Range images (depth maps) are seeing increased usage in a variety of application areas including entertainment, industrial automation, inspection, remote sensing, and military tactical planning. As the corpus of range imagery increases in size and the need to communicate such images over fixed-bandwidth channels increases, the compression of range data deserves investigation. Since the geometry encoded by range sensors is inherently "low-bandwidth", transform-based techniques seem appropriate for investigation in this context. This paper reports on experiments with a popular zerotree-based image codec (the SPIHT algorithm developed by Said and Pearlman) and its application to the compression of range imagery. Experiments suggest that compression rates of 1 bit/pixel and below are achievable with minimal impact on fidelity.

关键词： image coding Transform coding Codecs Optical sensors image storage Wavelet transforms Laboratories Automation Inspection remote sensing

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Improved back end for integer PCA and wavelet transforms for lossless compression of multispectral images

Improved back end for integer PCA and wavelet transforms for...

引用

International conference on pattern recognition

作者： J. Mielikainen A. Kaarna Department of Information Technology Lappeenranta University of Technology Luppeenranta Finland

remote sensing produces large amounts of digital data that is collected into databases. Since a variety of applications utilize multispectral data, the data cannot be compressed with lossy methods for some user communities. In this paper, we propose improvements for the combination of two reversible methods for the lossless compression of multispectral images. Our improvements are three-fold: number of bits allocated to the coefficients from PCA is not constant but it is based on heuristics, difference between consecutive coefficients are entropy-coded, also the back-end is modified so that all bands are separately entropy coded, i.e. instead of one entropy coder we used several. Depending on the AVIRIS image, the actual compression ratios, calculated from the files sizes, were in the range from 3.05 to 3.21.

关键词： Principal component analysis Wavelet transforms image coding Multispectral imaging Entropy image databases remote sensing Karhunen-Loeve transforms Information technology Extraterrestrial measurements

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Enhancing the performance of personal identity authentication systems by fusion of face verification experts

Enhancing the performance of personal identity authenticatio...

引用

IEEE International conference on Multimedia and Expo (ICME)

作者： J. Kittler M. Ballette J. Czyz F. Roli L. Vandendorpe Centre for Vision Speech and Signal Processing University of Surrey Guildford UK Department of Electrical Engineering University of Cagliari Italy Communications and Remote Sensing Laboratory Universite catholique de Louvain Belgium

We investigate the behavior knowledge space method (see Xu, L. et al., IEEE Transactions SMC, vol.22, no.3, p.418-35, 1992) and decision templates method (see Kuncheva, L. et al., pattern recognition, vol.34, p.299-314, 2001) of classifier fusion in the context of face verification. The study involves six experts which are not only correlated, but also their performance levels differ by as much as a factor of three. Through extensive experiments on the XM2VTS database using the Lausanne protocol, we found that the behavior knowledge space fusion strategy achieved consistently better results than the decision templates method. Most importantly, it exhibited quasi monotonic behavior as the number of experts combined increased. This is a very important conclusion, as it means that the performance of the multimodal system is not degraded by adding experts.

关键词： Authentication Biometrics Face detection Protocols image databases Error analysis Expert systems Speech processing Biomedical signal processing remote sensing

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Fixed and trained combiners for fusion of imbalanced pattern classifiers

Fixed and trained combiners for fusion of imbalanced pattern...

引用

International conference on Information Fusion

作者： F. Roli G. Fumera J. Kittler Department of Electrical and Electronic Engineering University of Cagliari Cagliari Italy Centre for Vision Speech and Signal Processing School of Electronics Computing and Mathematics University of Surrey Guildford UK

In the past decade, several rules for fusion of pattern classifiers' outputs have been proposed. Although imbalanced classifiers, that is, classifiers exhibiting very different accuracy, are used in many practical applications (e.g., multimodal biometrics for personal identity verification), the conditions of classifiers' imbalance under which a given rule can significantly outperform another one are not completely clear. In this paper, we experimentally compare various fixed and trained rules for fusion of imbalanced classifiers. The experiments are guided by the results of a previous theoretical analysis of the authors. Linear, order statistics-based, and trained combiners are compared by experiments on remote-sensing image data and on the X2M2VTS multimodal biometrics data base.

关键词： Biometrics Speech processing Bioinformatics Voting Biomedical signal processing Computer vision Mathematics remote sensing pattern classification Face

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Relative entropy-based methods for image thresholding

Relative entropy-based methods for image thresholding

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Jianwei Wang Eliza Yingzi Du Chein-I Chang P.D. Thouin Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore USA Department of Defense Fort Meade USA

A relative entropic thresholding approach was recently developed by Chang et al. (see pattern recognition, vol. 27, no. 9, p. 1275-1289, 1994). This paper extends Chang et al.'s approach to two more relative entropy-based thresholding methods, called local relative entropy thresholding (LRE) and joint relative entropy thresholding (JRE). Since relative entropy based methods are sensitive to sparse image histograms, a histogram compression and translation is suggested to compact the histogram. In order to achieve an objective assessment, uniformity and shape measures are introduced for performance evaluation. Experimental results show that when image histograms are sparse, with the proposed histogram compression and translation, JRE and LRE generally perform better than Chang et al.'s approach.

关键词： Entropy Histograms Shape measurement image coding remote sensing Signal processing image processing Computer science Hardware Inspection

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The fuzzy line between among and surround

The fuzzy line between among and surround

引用

IEEE International conference on Fuzzy Systems (FUZZ-IEEE)

作者： P. Matsakis S. Andrefouet Department of Computer Engineering and Computer Science University of Missouri Columbia Columbia MO USA College of Marine Science Remote Sensing and Biological Oceanography University of South Florida Saint Petersburg FL USA

Spatial relationships among image objects play a vital role in countless domains of computer vision (e.g., pattern recognition, image understanding, scene description). Some have received considerable attention the last few years (e.g., "to the right of," "above," "to the left of" and "below"), but others have not been the subject of as much investigation. In this paper, we design consistent fuzzy models of three important spatial relationships: "surrounded by," "between" and "among." These models are based on the histogram of forces, which represents the relative position between two objects. Here, force histograms are assimilated to fuzzy sets and processed through their /spl alpha/-cuts. Our goal is to extend the capabilities of a fuzzy system for linguistic scene description introduced in an earlier paper.

关键词： Histograms Layout Bismuth Computer vision pattern recognition Marine vehicles Biology computing Computer science Educational institutions remote sensing

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A Gauss-Markov model for hyperspectral texture analysis of urban areas

A Gauss-Markov model for hyperspectral texture analysis of u...

引用

International conference on pattern recognition

作者： G. Rellier X. Descombes J. Zerubia F. Falzon Ariana-projet commun CnrsAnriaNnsa INRIA Sophia-Antipolis France Alcatel Space Industries Cannes-La-Bocca France

In this paper we deal with the problem of texture segmentation using a joint spectral and spatial analysis of pixel distribution. Hyperspectral images are considered and, using a Markovian model, we develop a vectorial approach for this image type. A classification algorithm using this model was implemented for extracting and classifying urban areas. Results obtained from AVIRIS images are shown.

关键词： Gaussian processes Urban areas Hyperspectral imaging image texture analysis Hyperspectral sensors Pixel remote sensing Radiometry Performance analysis image resolution

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Edge and line detection in polarimetric SAR images

Edge and line detection in polarimetric SAR images

引用

International conference on pattern recognition

作者： D. Borghys V. Lacroix C. Perneel Signal & Image Centre Royal Military Academy Brussels Belgium

ISBN: (纸本)076951695X

A scheme for detecting edges and lines in multichannel SAR images is proposed. The line detector is constructed from the edge detector. The latter is based on multivariate statistical hypothesis tests applied to log-intensity SAR images. The raw results are vectorized by a traditional bright line extraction process. The scheme is illustrated by extracting dark linear structures on various full-polarimetric SAR images.

关键词： image edge detection Pixel Detectors Testing Speckle Infrared sensors Synthetic aperture radar remote sensing Satellites Data mining

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Atmospheric correction of spectral imagery: evaluation of the FLAASH algorithm with AVIRIS data

Atmospheric correction of spectral imagery: evaluation of th...

引用

Applied imagery pattern recognition Workshop (AIPR)

作者： M.W. Matthew S.M. Adler-Golden A. Berk G. Felde G.P. Anderson D. Gorodetzky S. Paswaters M. Shippert Spectral Sciences Inc. Burlington MA USA Space Vehicles Directorate Air Force Research Laboratory MA USA Research Systems Inc. Boulder CO USA

With its combination of good spatial and spectral resolution, visible to near infrared spectral imaging from aircraft or spacecraft is a highly valuable technology for remote sensing of the Earth's surface. Typically it is desirable to eliminate atmospheric effects on the imagery, a process known as atmospheric correction. We review the basic methodology of first-principles atmospheric correction and present results from the latest version of the FLAASH (fast line-of-sight atmospheric analysis of spectral hypercubes) algorithm. We show some comparisons of ground truth spectra with FLAASH-processed AVIRIS (airborne visible/infrared imaging spectrometer) data, including results obtained using different processing options, and with results from the ACORN (atmospheric correction now) algorithm that derive from an older MODTRAN4 spectral database.

关键词： Infrared imaging Infrared spectra Spatial resolution image resolution High-resolution imaging Optical imaging Aircraft Space vehicles Space technology remote sensing

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