Oct 11, 2012 · This letter presents a new technique for clustering hyperspectral images that exploits neighborhood-constrained spatial information.
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Abstract—This letter presents a new technique for clustering hyperspectral images that exploits neighborhood-constrained spa- tial information.
This letter presents a new technique for clustering hyperspectral images that exploits neighborhood-constrained spatial information.
In classifying very high spatial resolution (VHR) hyperspectral imagery, intra-class variation often adversely affects classification accuracy, mainly due to a ...
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A novel clustering algorithm named connection center evolution (CCE) has been proposed and achieved great success regarding this problem.
Mar 22, 2022 · In the present contribution, we propose an approach to spectral image segmentation combining hierarchical clustering and spatial constraints.
In this paper, a superpixel-level constraint representation (SPCR) model is proposed, combining a spatial constraint, simple linear iterative clustering (SLIC) ...
Mar 5, 2024 · The ccPGMM approach is applied to simulated datasets and real hyperspectral images of three types of puffed cereal, corn, rice, and wheat.
In this paper, we proposed the application of a Sequential Spectral Clustering (SSC) over the bipartite graph for remote sensing HSI clustering.
In classifying very high spatial resolution (VHR) hyperspectral imagery, intra-class variation often adversely affects classification accuracy, ...