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NOVEL HYPERSPECTRAL ANOMALY DETECTION METHODS BASED ON UNSUPERVISED NEAREST REGULARIZED SUBSPACE
Anomaly detection Hyperspectral imagery Unsupervised nearest regularized subspace Outlier Removal Local summation Dual-window sliding
2018/5/14
Anomaly detection has been of great interest in hyperspectral imagery analysis. Most conventional anomaly detectors merely take advantage of spectral and spatial information within neighboring pixels....
CLASSIFICATION OF PHOTOGRAMMETRIC POINT CLOUDS OF SCAFFOLDS FOR CONSTRUCTION SITE MONITORING USING SUBSPACE CLUSTERING AND PCA
Scaffolding components Photogrammetric point clouds Subspace clustering PCA Classification
2016/7/28
This paper presents an approach for the classification of photogrammetric point clouds of scaffolding components in a construction site, aiming at making a preparation for the automatic monitoring of ...
HYPERSPECTRAL IMAGE KERNEL SPARSE SUBSPACE CLUSTERING WITH SPATIAL MAX POOLING OPERATION
Hyperspectral image nonlinear processing spatial max pooling SSC kernel
2016/7/28
In this paper, we present a kernel sparse subspace clustering with spatial max pooling operation (KSSC-SMP) algorithm for hyperspectral remote sensing imagery. Firstly, the feature points are mapped f...
CLASSIFICATION OF POLARIMETRIC SAR IMAGE BASED ON THE SUBSPACE METHOD
Polarimetric SAR Classification subspace features
2014/4/24
Land cover classification is one of the most significant applications in remote sensing. Compared to optical sensing technologies,
synthetic aperture radar (SAR) can penetrate through clouds and hav...