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A Hyperspectral Image Classification Approach Based on Feature Fusion and Multi-Layered Gradient Boosting Decision Trees

Shenyuan Xu, Size Liu, Hua Wang, Wenjie Chen, Fan Zhang, Zhu Xiao
2020 Entropy  
This paper proposes a feature fusion and multi-layered gradient boosting decision tree model (FF-DT) for hyperspectral image classification.  ...  At present, many Deep Neural Network (DNN) methods have been widely used for hyperspectral image classification. Promising classification results have been obtained by utilizing such models.  ...  The combination of linear and nonlinear features is effective. The edge and contour information of the image is preserved.  ... 
doi:10.3390/e23010020 pmid:33375698 fatcat:kxixog6rqngrjkggvehbdrvliy

Visualization of Hyperspectral Images Using Bilateral Filtering

Ketan Kotwal, Subhasis Chaudhuri
2010 IEEE Transactions on Geoscience and Remote Sensing  
This paper presents a new approach for hyperspectral image visualization. A bilateral filtering-based approach is presented for hyperspectral image fusion to generate an appropriate resultant image.  ...  The proposed approach retains even the minor details that exist in individual image bands, by exploiting the edge-preserving characteristics of a bilateral filter.  ...  ACKNOWLEDGMENT The authors would like to thank the reviewers for their constructive suggestions and the Bharti Centre for Communication for the logistic support.  ... 
doi:10.1109/tgrs.2009.2037950 fatcat:nwn5nwgl3vdadjs4siow37dzfe

Spatial-spectral operator theoretic methods for hyperspectral image classification

John J. Benedetto, Wojciech Czaja, Julia Dobrosotskaya, Timothy Doster, Kevin Duke
2016 GEM - International Journal on Geomathematics  
In the work presented in this paper we consider the problem of spatial-spectral fusion for hyperspectral imagery.  ...  With the emergence of new remote sensing modalities, it becomes increasingly important to find novel algorithms for fusion and integration of different types of data for the purpose of improving performance  ...  Acknowledgments The authors would like to thank Professor Landgrebe (Purdue University, USA) for providing the Indian Pines data and Professor Paolo Gamba (Pavia University, Italy) for providing the Pavia  ... 
doi:10.1007/s13137-016-0085-0 fatcat:x6rnig3dwfbaho4wxjjf3oipom


M. Darvishnezhad, H. Ghassemian, M. Imani
2019 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
One of the challenges of the hyperspectral image classification is the fusing spectral and spatial features. There are several methods for fusing features in hyperspectral image classification.  ...  In this paper, to reducing extracted features from 3D-Gabor filters and increasing the classification accuracy in hyperspectral images, a novel method named Local Binary Graph (LBG) is used.  ...  Therefore, one of the application from hyperspectral images is the hyperspectral images classification.  ... 
doi:10.5194/isprs-archives-xlii-4-w18-285-2019 fatcat:rbzhlx6lvjhyfaq4u357y2smri


S. Xu, M. Ehlers
2017 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
This paper focuses on the application of Ehlers fusion to hyperspectral image sharpening.  ...  As the application of hyperspectral images is increasing, many researchers attempt to extend existing pansharpening techniques to hyperspectral images.  ...  Christine Pohl for her valuable and constructive feedback and the suggestions for this paper.  ... 
doi:10.5194/isprs-archives-xlii-2-w7-941-2017 fatcat:txipjcwwgzfbtgciq5wybfiusm

Processing of Multiresolution Thermal Hyperspectral and Digital Color Data: Outcome of the 2014 IEEE GRSS Data Fusion Contest

Wenzhi Liao, Xin Huang, Frieke Van Coillie, Sidharta Gautama, Aleksandra Pizurica, Wilfried Philips, Hui Liu, Tingting Zhu, Michal Shimoni, Gabriele Moser, Devis Tuia
2015 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
Index Terms-Hyperspectral, image analysis and data fusion (IADF), landcover classification, multimodal-, multiresolution-, multisource-data fusion, thermal imaging.  ...  The Contest was proposed as a double-track competition: one aiming at accurate landcover classification and the other seeking innovation in the fusion of thermal hyperspectral and color data.  ...  Schlerf (CRPGL) for their contribution of the Hyper-Cam LWIR sensor, and Dr. M. D. Martino (University of Genoa, Italy) for her contribution to data preparation.  ... 
doi:10.1109/jstars.2015.2420582 fatcat:khxvul3eyjcvfkeel7kbpmtdvq

Compressive data fusion for multi-sensor image analysis

Saurabh Prasad, Hao Wu, James E. Fowler
2014 2014 IEEE International Conference on Image Processing (ICIP)  
Multiple views of a scene-obtained via different sensing modalities-have the potential to significantly enhance image analysis for remote sensing and other applications.  ...  sensor fusion without the need for explicit reconstruction from compressive measurements.  ...  for direct image classification.  ... 
doi:10.1109/icip.2014.7026019 dblp:conf/icip/PrasadWF14 fatcat:cu56vi3iqffq5fzwloz2iyfzge

Multiscale Deep Spatial Feature Extraction Using Virtual RGB Image for Hyperspectral Imagery Classification

Liqin Liu, Zhenwei Shi, Bin Pan, Ning Zhang, Huanlin Luo, Xianchao Lan
2020 Remote Sensing  
In recent years, deep learning technology has been widely used in the field of hyperspectral image classification and achieved good performance.  ...  Meanwhile, we propose a multiscale feature fusion method to combine both the detailed and semantic characteristics, thus promoting the accuracy of classification.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs12020280 fatcat:lh6rwvsnrzhvhl2yk7zoetziym

Robust Hyperspectral Feature Extraction Method Using Edge Preserving Filters and Intrinsic Image Decomposition

Ali Can Karaca
2020 Journal of Aeronautics and Space Technologies (Havacilik ve Uzay Teknolojileri Dergisi)  
Spectral-spatial feature extraction methods present an effective way for classification of hyperspectral images.  ...  The proposed method first performs dimensionality reduction and then extracts features using multiple edge preserving filters and intrinsic image decomposition method.  ...  Parallel to this operation, edge preserving filters are applied to smooth band images while preserving edges and details.  ... 
doaj:8bfba9ca10fd41ef9f14bcdec3753332 fatcat:hqm5ehps35e63p3vmzce4rwony

Food Tray Sealing Fault Detection in Multi-Spectral Images Using Data Fusion and Deep Learning Techniques

Mohamed Benouis, Leandro D. Medus, Mohamed Saban, Abdessattar Ghemougui, Alfredo Rosado-Muñoz
2021 Journal of Imaging  
A correct food tray sealing is required to preserve food properties and safety for consumers. Traditional food packaging inspections are made by human operators to detect seal defects.  ...  Several pixel-based image fusion methods are proposed to obtain 2D images from the 3D hyperspectral image datacube, which feeds the deep learning (DL) algorithms.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/jimaging7090186 pmid:34564112 fatcat:2m6ji47aq5dipc7uyl6yvjbfia

Hyperspectral Image Classification with Multi-Scale Feature Extraction

Bing Tu, Nanying Li, Leyuan Fang, Danbing He, Pedram Ghamisi
2019 Remote Sensing  
regions of the image.  ...  Compared with other spectral-spatial classification methods, the proposed method can not only extract the characteristics of different scales, but also can better preserve detailed structures and the edge  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs11050534 fatcat:kckgybzop5eudgtpuvgjubmbqq

Extraction of tree crowns damaged by Dendrolimus tabulaeformis Tsai et Liu via spectral-spatial classification using UAV-based hyperspectral images

Ning Zhang, Yueting Wang, Xiaoli Zhang
2020 Plant Methods  
This article proposes a spectral-spatial classification framework that uses UAV-based hyperspectral images and combines a support vector machine (SVM) with an edge-preserving filter (EPF) for completing  ...  Unmanned aerial vehicle (UAV)-based hyperspectral imaging is effective for surveying and monitoring forest health.  ...  the guidance on UAV-hyperspectral image acquirement and preprocess.  ... 
doi:10.1186/s13007-020-00678-2 pmid:33062036 pmcid:PMC7547508 fatcat:hrmstwwjzfaj7inulr55fpk4gu

Spectral–Spatial Hyperspectral Image Classification With Edge-Preserving Filtering

Xudong Kang, Shutao Li, Jon Atli Benediktsson
2014 IEEE Transactions on Geoscience and Remote Sensing  
He is engaged in image fusion, image superresolution, pansharpening, and hyperspectral image classification.  ...  The integration of spatial context in the classification of hyperspectral images is known to be an effective way in improving classification accuracy.  ...  Falco for their contributions, and M. Pedergnana and Dr. J. Li for providing the software of the AEAP and the L-MLL methods.  ... 
doi:10.1109/tgrs.2013.2264508 fatcat:dee7r2s7qva73fthrxpgb33yx4

Hyperspectral edge filtering for measuring homogeneity of surface cover types

W.H. Bakker, K.S. Schmidt
2002 ISPRS journal of photogrammetry and remote sensing (Print)  
Edge operators are widely used on grey-level images as a first step in image segmentation or image interpretation.  ...  The problem remains on how to apply edge filtering on multispectral or even hyperspectral images. This paper presents a method that can be used for multispectral and hyperspectral edge filtering.  ...  Skidmore for kindly allowing the use of the HyMap data of Schiermonnikoog.  ... 
doi:10.1016/s0924-2716(02)00060-6 fatcat:yrebl6gfvjhhhkjkdhn6axuh2m

Stack Attention-Pruning Aggregates Multiscale Graph Convolution Networks for Hyperspectral Remote Sensing Image Classification

Na Liu, Bin Zhang, Qiuhuan Ma, Qingqing Zhu, Xiaoling Liu
2021 IEEE Access  
The hyperspectral remote sensing images are classified by traditional neural networks methods can achieve promising performance, but only operate on regular square regions with fixed.  ...  INDEX TERMS Hyperspectral remote sensing image classification, stack attention-pruning, multiscale graph convolution networks, longdistances joint interaction, multiscale spatial-temporal information,  ...  operations, and mask fusion layers (see parts e and f).  ... 
doi:10.1109/access.2021.3061489 fatcat:jqsobopyxnhb7ptvcldvepwk5e
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