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Browsing by Subject "Feature extraction"

Browsing by Subject "Feature extraction"

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    Blind Hyperspectral Unmixing using Autoencoders : A Critical Comparison 
    Pálsson, Burkni; Sveinsson, Jóhannes Rúnar; Úlfarsson, Magnús Örn (2022-01-01)
    Deep learning has shown to be a powerful tool and has heavily impacted the data-intensive field of remote sensing. As a result, the number of published deep learning-based spectral unmixing techniques is proliferating. Blind hyperspectral unmixing (HU) ...
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    Extinction Profiles for the Classification of Remote Sensing Data 
    Ghamisi, Pedram; Souza, Roberto; Benediktsson, Jon Atli; Zhu, Xiao Xiang; Rittner, Leticia (IEEE, 2016-07-18)
    Email Print Request Permissions With respect to recent advances in remote sensing technologies, the spatial resolution of airborne and spaceborne sensors is getting finer, which enables us to precisely analyze even small objects on the Earth. This ...
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    Feature Selection Based on Hybridization of Genetic Algorithm and Particle Swarm Optimization 
    Ghamisi, Pedram; Benediktsson, Jon Atli (IEEE Geoscience & Remote Sensing Society, 2015-02)
    A new feature selection approach that is based on the integration of a genetic algorithm and particle swarm optimization is proposed. The overall accuracy of a support vector machine classifier on validation samples is used as a fitness value. The new ...
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    Hyperspectral Feature Extraction Using Sparse and Smooth Low-Rank Analysis 
    Rasti, Behnood; Ghamisi, Pedram; Ulfarsson, Magnus (MDPI AG, 2019-01-10)
    In this paper, we develop a hyperspectral feature extraction method called sparse and smooth low-rank analysis (SSLRA). First, we propose a new low-rank model for hyperspectral images (HSIs) where we decompose the HSI into smooth and sparse components. ...
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    Invariant Attribute Profiles: A Spatial-Frequency Joint Feature Extractor for Hyperspectral Image Classification 
    Hong, Danfeng; Wu, Xin; Ghamisi, Pedram; Chanussot, Jocelyn; Yokoya, Naoto; Zhu, Xiao Xiang (Institute of Electrical and Electronics Engineers (IEEE), 2020-06)
    So far, a large number of advanced techniques have been developed to enhance and extract the spatially semantic information in hyperspectral image processing and analysis. However, locally semantic change, such as scene composition, relative position ...
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    A Survey on Spectral–Spatial Classification Techniques Based on Attribute Profiles 
    Ghamisi, Pedram; Dalla Mura, Mauro; Benediktsson, Jon Atli (IEEE, 2015)
    Just over a decade has passed since the concept of morphological profile was defined for the analysis of remote sensing images. Since then, the morphological profile has largely proved to be a powerful tool able to model spatial information (e.g., ...
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    Unsupervised and Supervised Feature Extraction Methods for Hyperspectral Images Based on Mixtures of Factor Analyzers 
    Zhao, Bin; Ulfarsson, Magnus; Sveinsson, Jóhannes Rúnar; Chanussot, Jocelyn (MDPI AG, 2020-04-07)
    This paper proposes three feature extraction (FE) methods based on density estimation for hyperspectral images (HSIs). The methods are a mixture of factor analyzers (MFA), deep MFA (DMFA), and supervised MFA (SMFA). The MFA extends the Gaussian mixture ...