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On the use of binary partition trees for the tree crown segmentation of tropical rainforest hyperspectral images
2015
Remote Sensing of Environment
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In this paper, we propose a method for hyperspectral image segmentation, based on the Binary Partition Tree (BPT) algorithm, and we apply it to two sites located in Hawaiian and Panamean tropical rainforests ...
The segmentation of remotely sensed images acquired over tropical forests is of great interest for numerous ecological applications, such as forest inventories or conservation and management of ecosystems ...
The third approach was based on the mean shift clustering (Comaniciu & Meer, 2002) of a RGB representation of the hyperspectral data. ...
doi:10.1016/j.rse.2014.12.020
fatcat:imcoh6a6u5bqxbjaguuztif6be
Multispectral Satellite Imagery Classification Using a Fuzzy Decision Tree
2014
Communications - Scientific Letters of the University of Zilina
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sensing application-oriented
A new algorithm for remote sensing multi- and hyperspectral informativity metrics entering into the algorithms.
imagery classification based on a fuzzy decision ...
to carry out this study and for the constructive
performance practical analysis of remote sensing hyperspectral discussion on the results obtained. ...
doi:10.26552/com.c.2014.1.109-113
fatcat:sthlynovyrapvneflaxuikgwa4
Spectral–Spatial Classification of Hyperspectral Imagery Based on Partitional Clustering Techniques
2009
IEEE Transactions on Geoscience and Remote Sensing
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The ISODATA algorithm and Gaussian mixture resolving techniques are used for image clustering. Experimental results are presented for two hyperspectral airborne images. ...
A new spectral-spatial classification scheme for hyperspectral images is proposed. ...
Landgrebe from Purdue University, USA, for providing the hyperspectral data. The authors would also like to thank I. Kåsen, T. V. Haavardsholm, and T. ...
doi:10.1109/tgrs.2009.2016214
fatcat:6he22digvnd6tmim5nvrbmsgxe
Chronological Advancement in Image Processing from Lime Stone Mofits to Superpixel Classification
2015
Journal of Computer Science
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While extracting the information from the remote sensed images the major issues that affect the accuracy of the classification is the presence of mixed pixels (reflecting more than one spectral signature ...
To get the information from the areas and objects which are not possible to be physically contact directly remote sensing image processing is used. ...
The data present in this article is not published anywhere else. This article is approved by corresponding author that there is no ethical issue in it. ...
doi:10.3844/jcssp.2015.1060.1074
fatcat:c7wkodloe5hltpnaoxh2xkvbte
Automatic Image Registration Through Image Segmentation and SIFT
2011
IEEE Transactions on Geoscience and Remote Sensing
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Automatic image registration (AIR) is still a present challenge for the remote sensing community. ...
In this paper, a new AIR method is proposed, based on the combination of image segmentation and SIFT, complemented by a robust procedure of outlier removal. ...
A similar performance with the k-means clustering technique for the four pairs of images was found. ...
doi:10.1109/tgrs.2011.2109389
fatcat:agdhbcw5qvdpfjmjx5mfatq2gu
Neuro-fuzzy Based Analysis of Hyperspectral Imagery
2008
Photogrammetric Engineering and Remote Sensing
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A geovisualization tool was developed to facilitate knowledge discovery and understanding of the hyperspectral image. A case study was conducted using a Hyperion image. ...
A neuro-fuzzy system, namely Gaussian Fuzzy Learning Vector Quantization (GFLVQ), was developed based on the synergy of a neural network and a fuzzy system. ...
Qi Li helped with the migration of the system from the UNIX system to the Windows ® environment. ...
doi:10.14358/pers.74.10.1235
fatcat:x4nd5pwrszhtjpldew2gcwrgmy
Automatic Framework for Spectral–Spatial Classification Based on Supervised Feature Extraction and Morphological Attribute Profiles
2014
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Without any doubt, classification (or mapping) can be considered as the backbone of most image interpretation in remote sensing. ...
However, most of the existing classification techniques have been developed for the analysis of multispectral images, and consequently, they are not usually efficient for the classification of hyperspectral ...
Gamba from the University of Pavia, Italy, for providing the ROSIS data and corresponding reference information and Dr. P. Marpu for his contributions. ...
doi:10.1109/jstars.2014.2298876
fatcat:nxj4xswdlvc3bb47wujib2lahi
Recent Advances in Forest Insect Pests and Diseases Monitoring Using UAV-Based Data: A Systematic Review
2022
Forests
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The purpose of this review is to summarize recent contributions and to identify knowledge gaps in UAV remote sensing for FIPD monitoring. ...
These machines provide flexibility, cost efficiency, and a high temporal and spatial resolution of remotely sensed data. ...
Acknowledgments: The authors would like to thank Cindy Santos, Luís Acevedo-Muñoz, João Rocha and Sérgio Fabres, for all their valuable comments and support. ...
doi:10.3390/f13060911
doaj:a077b5a200d744cbb9b504c1872e7739
fatcat:wzcqjv6rdvb5bm7nwfupozpxxm
Deep Learning in Remote Sensing: A Comprehensive Review and List of Resources
2017
IEEE Geoscience and Remote Sensing Magazine
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In this article, we analyze the challenges of using deep learning for remote sensing data analysis, review the recent advances, and provide resources to make deep learning in remote sensing ridiculously ...
There are controversial opinions in the remote sensing community. ...
The output of the SAE is used as a feature in the final step for k-nearest neighbor clustering of superpixels. Zhang et al. ...
doi:10.1109/mgrs.2017.2762307
fatcat:ec7b32lpdnhvzbdz2uoayw6anq
Damage assessment framework for landslide disaster based on very high-resolution images
2016
Journal of Applied Remote Sensing
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Based on an analysis of very high-resolution remote-sensing images, we propose an automatic building damage assessment framework for rainfall-or earthquake-induced landslide disasters. ...
Damage assessment framework for landslide disaster based on very high-resolution images," Abstract. ...
Acknowledgments This research was primarily supported by the National Natural Science Foundation of China ...
doi:10.1117/1.jrs.10.025027
fatcat:qelow3lu75glphm7s2rmjptdgq
Recognition of Bloom/Yield in Crop Images Using Deep Learning Models for Smart Agriculture: A Review
2021
Agronomy
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Remote sensing technologies offer accuracy and reliability in crop yield prediction and estimation. ...
The yield of a crop may vary from year to year depending on the variations in climate, soil parameters and fertilizers used. ...
The multispectral and hyperspectral images acquired through remote sensing were used for monitoring seasonally variable crop and soil status features such as crop diseases, crop biomass, the nitrogen content ...
doi:10.3390/agronomy11040646
fatcat:n3ru7ggspvgixlcu24meshbax4
Hyperspectral Image Representation and Processing With Binary Partition Trees
2013
IEEE Transactions on Image Processing
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Based on region-merging techniques, the BPT construction is investigated by studying the hyperspectral region models and the associated similarity metrics. ...
This paper proposes the construction and the processing of a new region-based hierarchical hyperspectral image representation relying on the binary partition tree (BPT). ...
Fauvel for his support in performing the spectral-spatial classification comparison. ...
doi:10.1109/tip.2012.2231687
pmid:23221824
fatcat:lfufcjxdwrfu5biwlmpfssdkyi
Reducing the Complexity of Genetic Fuzzy Classifiers in Highly-Dimensional Classification Problems
2012
International Journal of Computational Intelligence Systems
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Comparative results in a hyperspectral remote sensing classification as well as in 12 real-world classification datasets indicate the effectiveness of the proposed methodology in generating high-performing ...
The REA is performed in two successive steps: the first one selects the relevant features of the currently extracted rule, whereas the second one decides the antecedent part of the fuzzy rule, using the ...
Application in Hyperspectral Remote Sensing Classification Remote sensing classification from hyperspectral satellite images is an arduous task, because of the large number of features involved and the ...
doi:10.1080/18756891.2012.685290
fatcat:d4rcvwjw3vh6blavulq5o33zfq
Recent Advances in Unmanned Aerial Vehicles Forest Remote Sensing—A Systematic Review. Part II: Research Applications
2021
Forests
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acquiring tree spectral signature especially for pest and diseases detection, (2) automatic processes for image analysis are poorly flexible or based on proprietary software at the expense of flexible ...
Due to the progress in platforms and sensors and the opening of the dedicated market, unmanned aerial vehicle–remote sensing (UAV–RS) is improving its key role in the forestry sector as a tool for sustainable ...
Basing on a rigorous review, results are elaborated to address the pivotal research questions for the set of studies, previously clustered by six forestry topics. ...
doi:10.3390/f12040397
fatcat:6mtlejuku5c3xbx2eq7inpdjse
Noise-Tolerant Deep Neighborhood Embedding for Remotely Sensed Images with Label Noise
2021
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Recently, many deep learning-based methods have been developed for solving remote sensing (RS) scene classification or retrieval tasks. ...
Our experiments, conducted on two benchmark RS datasets, validate the effectiveness of the proposed approach on three different RS scene interpretation tasks, including classification, clustering, and ...
INTRODUCTION W ITH the rapid development of satellite sensors, remote sensing (RS) has entered the big data era. ...
doi:10.1109/jstars.2021.3056661
fatcat:h6vv4f7rfrhtpjchpqn4u63poq
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