PCA-based feature reduction for hyperspectral remote sensing image classification
The hyperspectral remote sensing images (HSIs) are acquired to encompass the essential
information of land objects through contiguous narrow spectral wavelength bands. The …
information of land objects through contiguous narrow spectral wavelength bands. The …
Information-theoretic feature selection with segmentation-based folded principal component analysis (PCA) for hyperspectral image classification
Hyperspectral image (HSI) usually holds information of land cover classes as a set of many
contiguous narrow spectral wavelength bands. For its efficient thematic mapping or …
contiguous narrow spectral wavelength bands. For its efficient thematic mapping or …
Effective feature extraction through segmentation-based folded-PCA for hyperspectral image classification
The remote sensing hyperspectral images (HSIs) usually comprise many important
information of the land covers capturing through a set of hundreds of narrow and contiguous …
information of the land covers capturing through a set of hundreds of narrow and contiguous …
[HTML][HTML] Mutual information-driven feature reduction for hyperspectral image classification
A hyperspectral image (HSI), which contains a number of contiguous and narrow spectral
wavelength bands, is a valuable source of data for ground cover examinations …
wavelength bands, is a valuable source of data for ground cover examinations …
NDVI based change detection in Sundarban Mangrove Forest using remote sensing data
As a global ecosystem, Sundarban mangrove forest plays a significant role by tackling
enormous CO 2, and other environmental impurities from air and water. It also protects …
enormous CO 2, and other environmental impurities from air and water. It also protects …
Improved folded-PCA for efficient remote sensing hyperspectral image classification
Hyperspectral images (HSIs) contain notable information of land objects by acquiring an
immense set of narrow and contiguous spectral bands. Feature extraction (FE) and feature …
immense set of narrow and contiguous spectral bands. Feature extraction (FE) and feature …
Effective subspace detection based on the measurement of both the spectral and spatial information for hyperspectral image classification
Subspace detection from high dimensional hyperspectral image (HSI) data cube has
become an important area of research for efficient identification of ground objects. Standard …
become an important area of research for efficient identification of ground objects. Standard …
An efficient lossless compression technique for remote sensing images using segmentation based band reordering heuristics
The size of remote sensing (RS) image is indeed massive due to hundreds capturing
wavelengths bands used for collecting information about the ground surface. The data in the …
wavelengths bands used for collecting information about the ground surface. The data in the …
A lightweight 3D-2D convolutional neural network for spectral-spatial classification of hyperspectral images
Hyperspectral Image (HSI) is usually composed of hundreds of capturing wavelength bands,
which not only increase the size of the HSI rapidly but also impose various obstacles in …
which not only increase the size of the HSI rapidly but also impose various obstacles in …
Segmentation-based truncated-SVD for effective feature extraction in hyperspectral image classification
Remote sensing hyperspectral images (HSIs) are rich sources of information about land
cover captured across hundreds of narrow, contiguous spectral wavelength bands …
cover captured across hundreds of narrow, contiguous spectral wavelength bands …