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 …
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 …
Hyperspectral image classification via information theoretic dimension reduction
Hyperspectral images (HSIs) are one of the most successfully used tools for precisely and
potentially detecting key ground surfaces, vegetation, and minerals. HSIs contain a large …
potentially detecting key ground surfaces, vegetation, and minerals. HSIs contain a large …
Spectral segmentation based dimension reduction for hyperspectral image classification
Hyperspectral images (HSI) contain a wide range of information, the most prominent
technology for observing the earth. However, using an original HSI high-dimensional …
technology for observing the earth. However, using an original HSI high-dimensional …
Feature reduction of hyperspectral image for classification
Informative feature extraction from hyperspectral image (HSI) is the primary and most
challenging task in the hyperspectral data processing. The rich source of HSI information …
challenging task in the hyperspectral data processing. The rich source of HSI information …
Analysis of PCA based feature extraction methods for classification of hyperspectral image
Hyperspectral Image (HSI) is a rich source of information for the analysis of the earth's
surface. HSI produces a rich set of both spectral and spatial information for possible …
surface. HSI produces a rich set of both spectral and spatial information for possible …
Hyperspectral images classification and dimensionality reduction using spectral interaction and svm classifier
A Elmaizi, E Sarhrouni, A Hammouch… - arXiv preprint arXiv …, 2022 - arxiv.org
Over the past decades, the hyperspectral remote sensing technology development has
attracted growing interest among scientists in various domains. The rich and detailed …
attracted growing interest among scientists in various domains. The rich and detailed …
Feature Subspace Detection for Hyperspectral Images Classification using Segmented Principal Component Analysis and F-score
UAME Ali, MA Hossain - 2020 IEEE Region 10 Symposium …, 2020 - ieeexplore.ieee.org
Remotely sensed images provide unseen characteristics of the earth's surface as they are
composed of hundreds of spectral bands of the electromagnetic spectrum. Both spatial and …
composed of hundreds of spectral bands of the electromagnetic spectrum. Both spatial and …
Spectral subset detection for hyperspectral image classification
Remote sensing hyperspectral image (HSI) is one of the emerging technologies for the
possible recognition and specific identification of necessary minerals, vegetation, synthetic …
possible recognition and specific identification of necessary minerals, vegetation, synthetic …