805 Hits in 2.5 sec


P. Javadi
2015 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
The spectral unmixing method that implemented here is an effective technique for classifying a hyperspectral image giving the classification accuracy about 89%.  ...  The results of classification when applying on the original images are not good because some of the hyperspectral image bands are subject to absorption and they contain only little signal.  ...  The analysis part is a key component of RS system, because we can change the data to information via it.  ... 
doi:10.5194/isprsarchives-xl-1-w5-343-2015 fatcat:dwmepv55ivguxcm3uh6iwj6mhm

Nonlocal Total Variation Subpixel Mapping for Hyperspectral Remote Sensing Imagery

Ruyi Feng, Yanfei Zhong, Yunyun Wu, Da He, Xiong Xu, Liangpei Zhang
2016 Remote Sensing  
[39], image classification [40], sparse unmixing [41] , and so on.  ...  In this paper, a novel subpixel mapping method for hyperspectral remote sensing imagery based on a nonlocal method, namely nonlocal total variation subpixel mapping (NLTVSM), is proposed to use the nonlocal  ...  Figure 11 . 11 The subpixel mapping results for the Nuance hyperspectral image. (a) Reference classification image; (b) SASM; (c) PSSM; (d) GASM; (e) GSM; (f) TVSM; and (g) NLTVSM.  ... 
doi:10.3390/rs8030250 fatcat:gvkevxixdraydnwbzc6xzjnrfa

Low-bit rate exploitation-based lossy hyperspectral image compression

Chein-I Chang
2010 Journal of Applied Remote Sensing  
In order to demonstrate advantages of the proposed spectral/spatial compression approach applications of subpixel target detection and mixed pixel analysis are used for experiments for performance evaluation  ...  Unfortunately, some major issues generally encountered in hyperspectral data exploitation at low or very low-bit rate compression, for example, subpixels and mixed pixels which do not occur in traditional  ...  -I Chang would like to thank for support received from the National Science Council in Taiwan under NSC 98-2811-E-005-024 and NSC 98-2221-E-005-096.  ... 
doi:10.1117/1.3530429 fatcat:2f72oxaiwbd2tju45umqfy5zyi

Subpixel target detection and enhancement in hyperspectral images

K. C. Tiwari, M. Arora, D. Singh, Sylvia S. Shen, Paul E. Lewis
2011 Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVII  
This limits the applicability of hyperspectral data for subpixel target detection.  ...  Hyperspectral data due to its higher information content afforded by higher spectral resolution is increasingly being used for various remote sensing applications including information extraction at subpixel  ...  However, multifold increase in data, spectral variability and lack of adequate spatial resolution have given rise to a number of typical problems in hyperspectral image analysis for subpixel target detection  ... 
doi:10.1117/12.887426 fatcat:a3ud2j5du5frvd2meq2gvcyw4y

Hyperspectral image quality for unmixing and subpixel detection applications

John P. Kerekes, Daniel S. Goldberg, Peter D. Burns, Sophie Triantaphillidou
2013 Image Quality and System Performance X  
Initial results of our study show the dominance of spatial resolution in determining the ability to detect subpixel objects and the necessity of sufficient spectral range for unmixing accuracy.  ...  Future work is aimed at generalizing these results and to provide new prediction tools to assist with hyperspectral imaging sensor design and operation.  ...  ACKNOWLEDGMENTS The authors would like to acknowledge the efforts of several colleagues in fabricating, deploying, and measuring ground truth for the targets used in the experiment: Bo Ding, Kim Horan,  ... 
doi:10.1117/12.2001693 fatcat:am4urcxnq5fmjlkbyhq7v6hg3i

An Adaptive Subpixel Mapping Method Based on MAP Model and Class Determination Strategy for Hyperspectral Remote Sensing Imagery

Yanfei Zhong, Yunyun Wu, Xiong Xu, Liangpei Zhang
2015 IEEE Transactions on Geoscience and Remote Sensing  
, AMCDSM, is proposed for hyperspectral remote sensing imagery.  ...  Traditional subpixel mapping algorithms only utilize the low-resolution image obtained by the classification image downsampling and do not consider the spectral unmixing error, which is difficult to account  ...  Shen of Wuhan University, Wuhan, China, for providing the helpful suggestions.  ... 
doi:10.1109/tgrs.2014.2340734 fatcat:xcjgk4gefbapzhpl6vwou7qfi4

Editorial for Special Issue "Hyperspectral Imaging and Applications"

Chein-I Chang, Meiping Song, Junping Zhang, Chao-Cheng Wu
2019 Remote Sensing  
This Special Issue has accepted and published 25 papers in various areas, which can be organized into 7 categories, Data Unmixing, Spectral variability, Target Detection, Hyperspectral Image Classification  ...  Many problems, which cannot be resolved by multispectral imaging, can now be solved by hyperspectral imaging.  ...  Qu This paper develops a Component substitution (CS) and multiresolution analysis (MRA)-based hybrid framework based on intrinsic image decomposition and weighted least squares filter for hyperspectral  ... 
doi:10.3390/rs11172012 fatcat:c23u3rahgjhctowk5xwllt2qea


Zhaoxin Liu, Liaoying Zhao, Xiaorun Li, Shuhan Chen
2018 ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
index analysis.  ...  Owing to the limitation of spatial resolution of the imaging sensor and the variability of ground surfaces, mixed pixels are widesperead in hyperspectral imagery.  ...  INTRODUCTION Hyperspectral images have become one of the most important information sources for earth observation.  ... 
doi:10.5194/isprs-annals-iv-3-161-2018 fatcat:lqryhdpf2fh5zp7f5wgbpy376e

Down-scaling of satellite hyperspectral images for monitoring croplands

Eunyoung Choe, SukYoung Hong, YiHyun Kim
2010 2010 IEEE International Geoscience and Remote Sensing Symposium  
This down-scaled hyperspectral image could show better analysis results of soil properties, crop residues, and vegetation types and enhance their mapping accuracy without loss of spectral information.  ...  Geocoding was implemented between Hyperion and QuickBird image before the classification steps.  ... 
doi:10.1109/igarss.2010.5649715 dblp:conf/igarss/ChoeHK10 fatcat:wbnmks6vj5ehfblihhphrcnary

Fuzzy Based Hyperspectral Image Segmentation Using Subpixel Detection[

Veera SenthilKumar.G, Dhivya. M, Sivasangari. R, Suganya. V
2014 International Journal of Information Sciences and Techniques  
Principal Component Analysis (PCA) is the basic step adopted to reduce the high dimensional data of image to low dimensional data.  ...  Keywords Spectral analysis, Hyperspectral image segmentation, Sub-pixel detection and FCM.  ...  Subpixel analysis has detected targets covering as small as 1-3 % of the pixel.  ... 
doi:10.5121/ijist.2014.4322 fatcat:emizzvytrrg2hpvzllqwo3itam


I. Ronay, F. Kizel, R. Lati
2022 ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
In this regard, hyperspectral sensors can capture leaf anatomy and biochemistry variations, suggesting many advantages for weed classification.  ...  However, the typical tradeoff between spectral and spatial resolution poses a challenge for applying hyperspectral imaging in large scales and scenarios of high densities and tiny seedlings at early growth  ...  Then, we selected the first ten components of the hyperspectral data and used them for the SVM classification.  ... 
doi:10.5194/isprs-annals-v-3-2022-477-2022 fatcat:y6plb2d3nbhsjfyarszvdllz7q

Super-resolution land-cover mapping based on the selective endmember spectral mixture model in hyperspectral imagery

Liangpei Zhang
2011 Optical Engineering: The Journal of SPIE  
Endmember is a fundamental variable in the process, which is a critical issue for decomposing the mixed pixels and sharpening the subpixel level images.  ...  Two different types of hyperspectral data are used in our experiments. First, the SESM model is tested individually for validation of its applicability.  ...  Super-Resolution Mapping Method The output of the soft classification for each pixel was an estimate of the proportion of the component classes, which does not indicate the location of the subpixel component  ... 
doi:10.1117/1.3660527 fatcat:3fwvjwpkxfdg7own3kbnlcel34

Attraction-Repulsion Model-Based Subpixel Mapping of Multi-/Hyperspectral Imagery

Xiaohua Tong, Xue Zhang, Jie Shan, Huan Xie, Miaolong Liu
2013 IEEE Transactions on Geoscience and Remote Sensing  
In the experiment, both a synthetic image with known fractional abundances and an EO-1 Hyperion hyperspectral image of Shanghai were used to evaluate performances of the subpixel mapping methods.  ...  The proposed method is formulated as an optimization problem with respect to attractionrepulsion among subpixels and is used to reconstruct a finer spatial resolution image from a lower resolution one.  ...  Among the most common techniques for subpixel-based soft classification are independent component analysis [5] , [6] , the conventional spectral angle mapper [7] , linear spectral mixture analysis  ... 
doi:10.1109/tgrs.2012.2218612 fatcat:gm2hr6ofzve7reb7tn2ajijymq

Detection and correction of spectral and spatial misregistrations for hyperspectral data using phase correlation method

Naoto Yokoya, Norihide Miyamura, Akira Iwasaki
2010 Applied Optics  
Hyperspectral imaging sensors suffer from spectral and spatial misregistrations. These artifacts prevent the accurate acquisition of spectra and thus reduce classification accuracy.  ...  The main objective of this work is to detect and correct spectral and spatial misregistrations of hyperspectral images. The Hyperion visible near-infrared (VNIR) subsystem is used as an example.  ...  Methods of evaluating hyperspectral sensor characteristics are also described. Subpixel Image Registration Methods Subpixel image registration methods can detect smile and keystone properties.  ... 
doi:10.1364/ao.49.004568 pmid:20733628 fatcat:bezdfadjsrebfekwgh4es64zy4

Advances in Hyperspectral Image and Signal Processing: A Comprehensive Overview of the State of the Art

Pedram Ghamisi, Naoto Yokoya, Jun Li, Wenzhi Liao, Sicong Liu, Javier Plaza, Behnood Rasti, Antonio Plaza
2017 IEEE Geoscience and Remote Sensing Magazine  
This paper offers a comprehensive tutorial/overview focusing specifically on hyperspectral data analysis, which is categorized into seven broad topics: classification, spectral unmixing, dimensionality  ...  Hence, rigorous and innovative methodologies are required for hyperspectral image and signal processing and have become a center of attention for researchers worldwide.  ...  In addition, the authors would like to thank the National Center for Airborne Laser Mapping (NCALM) at the University of Houston for providing the CASI Houston data set, and the IEEE GRSS Image Analysis  ... 
doi:10.1109/mgrs.2017.2762087 fatcat:6ezzye7yyvacbouduqv2f2c7gi
« Previous Showing results 1 — 15 out of 805 results