Detecting and monitoring landslides are hot topics in remote sensing community, particularly
with the development of remote sensing technologies and the significant progress of …

Soil spectra are often measured in the laboratory, and there is an increasing number of large-
scale soil spectral libraries establishing across the world. However, calibration models …

The locality preserving projections (LPP) algorithm is a recently developed linear
dimensionality reduction algorithm that has been frequently used in face recognition and …

Remote sensing image classification is a common application of remote sensing images. In
order to improve the performance of Remote sensing image classification, multiple classifier …

Hyperspectral imaging is a popular tool used for non-invasive plant disease detection. Data
acquired with it usually consist of many correlated features; hence most of the acquired …

Hyperspectral target detection is widely used in both military and civilian fields. In practical
applications, how to select a low-correlation and representative band subset to reduce …

In this letter, we proposed a novel band selection algorithm for hyperspectral images (HSIs)
based on column subset selection. The main idea of the proposed algorithm comes from the …

Hyperspectral images are one of the most important fundamental and strategic information
resources, imaging the same ground object with hundreds of spectral bands varying from …

The influence of line-broadening and zero shift of the sensor on identifying spectral lines
was eliminated by an improved K-medoids clustering algorithm after performing principal …

Hyperspectral imaging techniques are widely used in cultural heritage for documentation
and material analysis. A pigment classification of an artwork is an essential task. Several …