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检索条件"机构=Laboratory of Applied Remote Sensing and Image Processing"

共 196 条记录，以下是61-70 订阅

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A structure tensor for hyperspectral images

A structure tensor for hyperspectral images

引用

3rd Workshop on Hyperspectral image and Signal processing: Evolution in remote sensing, WHISPERS 2011

作者： Marin-Mcgee, Maider Velez-Reyes, Miguel Laboratory for Applied Remote Sensing and Image Processing University of Puerto Rico Mayaguez Puerto Rico

In this article, a structure tensor for hyperspectral images (HSI) is proposed. A weighted zero mean smoothed gradient to calculate the initial matrix field is used. The weights are constructed from the zero mean data by comparison with a normalized absolute value of the median. The problem with the classical definition is the assumption that all bands provide the same amount of edge information giving them the same weights. As a result many non-edge pixels are reinforced producing false edges. Therefore, other processes that depend on the structure tensor will be misguided. The proposed weights are selected from pixel's spectral values that are greater than and closely around the absolute value of the median, reinforcing only the better candidates in the spectra to be edges in their respective spectral interval, therefore making the structure tensor a better edge discriminator. Comparisons of this method with the standard definition of the structure tensor and results of using the proposed method for nonlinear tensor anisotropic diffusion are presented. © 2011 IEEE.

关键词： Tensors

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Multi-temporal unmixing analysis of Hyperion images over the Guanica Dry Forest

Multi-temporal unmixing analysis of Hyperion images over the...

引用

3rd Workshop on Hyperspectral image and Signal processing: Evolution in remote sensing, WHISPERS 2011

作者： Torres-Madronero, Maria C. Velez-Reyes, Miguel Van Bloem, Skip J. Chinea, Jesus D. Laboratory for Applied Remote Sensing and Image Processing University of Puerto Rico Mayaguez Puerto Rico

This paper presents a methodology to analyze time-series data from Hyperion to study seasonal vegetation dynamics on the Gunica Dry Forest in Puerto Rico. Unmixing analysis is performed over ten near-cloud-free Hyperion images collected in different months in 2008. Abundance maps and endmembers estimated from the unmixing procedure are used to analyze the seasonal changes in the forest. Results from the analysis are compared with published knowledge of the Guanica Forest phenology. © 2011 IEEE.

关键词： Forestry

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A structure tensor for hyperspectral images

A structure tensor for hyperspectral images

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Workshop on Hyperspectral image and Signal processing: Evolution in remote sensing, WHISPERS

作者： Maider Marin-McGee Miguel Velez-Reyes Laboratory of Applied Remote Sensing and Image Processing University of Puerto Rico Mayaguez USA

关键词： Tensile stress Equations image edge detection Mathematical model Anisotropic magnetoresistance Symmetric matrices Hyperspectral imaging

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Multi-temporal unmixing analysis of Hyperion images over the Guanica Dry Forest

Multi-temporal unmixing analysis of Hyperion images over the...

引用

Workshop on Hyperspectral image and Signal processing: Evolution in remote sensing, WHISPERS

作者： Maria C. Torres-Madronero Miguel Velez-Reyes Skip J. Van Bloem Jesus D. Chinea Laboratory of Applied Remote Sensing and Image Processing University of Puerto Rico Mayaguez USA

This paper presents a methodology to analyze time-series data from Hyperion to study seasonal vegetation dynamics on the Guánica Dry Forest in Puerto Rico. Unmixing analysis is performed over ten near-cloud-free Hyperion images collected in different months in 2008. Abundance maps and endmembers estimated from the unmixing procedure are used to analyze the seasonal changes in the forest. Results from the analysis are compared with published knowledge of the Guanica Forest phenology.

关键词： Vegetation mapping Soil Reflectivity Hyperspectral imaging Indexes

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Edge enhancement algorithm based on the wavelet transform for automatic edge detection in SAR images

Edge enhancement algorithm based on the wavelet transform fo...

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作者： Tello Alonso, Mariv Lopez-Martinez, Carlos Mallorqui, Jordi J. Salembier, Philippe Remote Sensing Laboratory Department of Signal Theory and Communications Universitat Politcnica de Catalunya Barcelona 08034 Spain Image and Video Processing Group Department of Signal Theory and Communications Universitat Politcnica de Catalunya Barcelona 08034 Spain

This paper presents a novel technique for automatic edge enhancement and detection in synthetic aperture radar (SAR) images. The characteristics of SAR images justify the importance of an edge enhancement step prior to edge detection. Therefore, this paper presents a robust and unsupervised edge enhancement algorithm based on a combination of wavelet coefficients at different scales. The performance of the method is first tested on simulated images. Then, in order to complete the automatic detection chain, among the different options for the decision stage, the use of geodesic active contour is proposed. The second part of this paper suggests the extraction of the coastline in SAR images as a particular case of edge detection. Hence, after highlighting its practical interest, the technique that is theoretically presented in the first part of this paper is applied to real scenarios. Finally, the chances of its operational capability are assessed. © 2006 IEEE.

关键词： Edge detection

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Identifiability of geometric models for linear unmixing at different spatial resolutions in hyperspectral unmixing

Identifiability of geometric models for linear unmixing at d...

引用

Workshop on Hyperspectral image and Signal processing

作者： Santos-García, Andrea Velez-Reyes, Miguel Laboratory for Applied Remote Sensing and Image Processing University of Puerto Rico-Mayagüez Puerto Rico

ISBN: (纸本)9781424489077

Proposed and existing hyperspectral remote sensors, provide information about the scene of interest at resolutions ranging from few meters to few kilometers in terrestrial and space applications. Understanding the type of information extracted with image exploitation algorithms and how does it relates to actual spectra on the ground are important problems when we look into algorithms that perform unmixing of hyperspectral images for subpixel analysis. In this paper, we investigate how spatial resolution affects the capability of unmixing algorithms based on geometric models to extract information from a scene. We study the performance of the positive matrix factorization for unmixing of hyperspectral at different spatial resolutions and how does it compare with other approaches such as MaxD, and SMACC. Hyperspectral imagery collected using the AISA sensor at 1m and 4m are used for the experiments. The results obtained illustrate some of the effects that algorithms assumptions have on unmixing results. ©2010 IEEE.

关键词： Space applications

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A vector SIFT operator for interest point detection in hyperspectral imagery

A vector SIFT operator for interest point detection in hyper...

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Workshop on Hyperspectral image and Signal processing

作者： Dorado-Muñoz, Leidy P. Velez-Reyes, Miguel Mukherjee, Amit Roysam, Badrinath Laboratory for Applied Remote Sensing and Image Processing University of Puerto Rico-Mayaguez PR United States Electrical Computer and Systems Engineering Department Rensselaer Polytechnic Institute NY United States

ISBN: (纸本)9781424489077

An algorithm for automated extraction of interest points (IP) in hyperspectral images is presented. IP are features of the image that capture information from its neighbors and are distinctive and stable under translation and rotation. IP operators for gray level images were proposed more than a decade ago and have since been studied extensively. IP are helpful in data reduction to reduce the computational burden of various algorithms by replacing an exhaustive search over the entire image domain by a probe into a concise set of highly informative points. The vector SIFT approach extends Lowe's IP operator that uses local extrema of Difference of Gaussian at multiple scales to detect interest point in gray level images by direct conversion of scalar operations such as scale-space generation, and extreme point detection into operations that take the vector nature of the image into consideration. Vector anisotropic diffusion is used for scale-space generation which enhances edges and improves IP detection. Experiments with hyperspectral images of different spatial resolutions and evaluation of IP found based on image registration is presented. ©2010 IEEE.

关键词： Vectors

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Identifiability of geometric models for linear unmixing at different spatial resolutions in hyperspectral unmixing

Identifiability of geometric models for linear unmixing at d...

引用

Workshop on Hyperspectral image and Signal processing: Evolution in remote sensing, WHISPERS

作者： Andrea Santos-García Miguel Velez-Reyes Laboratory of Applied Remote Sensing and Image Processing University of Puerto Rico MayagÜez Puerto Rico

关键词： Pixel Hyperspectral imaging Spatial resolution Roads

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A vector SIFT operator for interest point detection in hyperspectral imagery

A vector SIFT operator for interest point detection in hyper...

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Workshop on Hyperspectral image and Signal processing: Evolution in remote sensing, WHISPERS

作者： Leidy P. Dorado-Muñoz Miguel Velez-Reyes Amit Mukherjee Badrinath Roysam Laboratory of Applied Remote Sensing and Image Processing University of Puerto Rico Puerto Rico Electrical Computer and Systems Engineering Department Rensselaer Polytechnic Institute NY USA

关键词： Hyperspectral imaging Pixel Detectors Feature extraction image edge detection IP networks

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Digital camera calibration method based on PhotoModeler

Digital camera calibration method based on PhotoModeler

引用

2010 3rd International Congress on image and Signal processing, CISP 2010

作者： Zhang, Weizheng Jiang, Tao Han, Mingqin Image Processing Department Information and Electrical College Shandong University of Science and Technology Qingdao China Remote Sensing Department Geometrics College Shandong University of Science and Technology Qingdao China Key Laboratory of Surveying and Mapping Technology on Island and Reed State Bureau of Surveying and Mapping Qingdao China

ISBN: (纸本)9781424465149

In recent years, with CCD (or CMOS) image sensor as the core components, digital cameras turns into a new generation cameras. Compared with ordinary cameras, digital cameras have a distinct advantage: achieving digital information collection, image processing conveniently, and have been widely used in many fields presently. However, when people using ordinary digital camera doing research, few consider the error of the target image caused by digital camera distortion, digital camera is the important equipment to obtain digital image data, and its camera distortion should attract users attention. To ensure the quality of its results to meet the precision of the measurement tasks, the calibration of each parameter will be an important task. Commonly used camera calibration method including: spatial resection, direct linear transformation, analytical plumb line and self calibration. In this paper we use space resection, obtain calibration images through the establishment of mathematical model calibration, locate the accurate position of pixels and obtain accurate calibration parameters. Getting conclusion by authentication example, provide basic guarantees for the follow-up of Digital close-range photogrammetry and 3D modeling. ©2010 IEEE.

关键词： Digital cameras

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