The agriculture sector is one of the backbones of many countries' economies. Its processes
have been changing to enable technology adoption to increase productivity, quality, and …

This article gives a survey of state-of-the-art methods for processing remotely sensed big
data and thoroughly investigates existing parallel implementations on diverse popular high …

Hyperspectral imaging (HSI) is a competitive remote sensing technique in several fields,
from Earth observation to health, robotic vision, and quality control. Each HSI scene contains …

Rapid advancement in the development of hyperspectral image analysis techniques has led
to specialized hyperspectral missions. It results in the bulk transmission of hyperspectral …

The Consultative Committee for Space Data Systems (CCSDS) published the CCSDS 123.0-
B-2,“Low-Complexity Lossless and Near-Lossless Multispectral and Hyperspectral Image …

Multispectral imaging (MI) techniques are being used very often to identify different
properties of nature in several domains, going from precision agriculture to environmental …

Machine learning techniques are widely used for pixel-wise classification of hyperspectral
images. These methods can achieve high accuracy, but most of them are computationally …

Hyperspectral imaging is an indispensable technology for many remote sensing
applications, yet expensive in terms of computing resources. It requires significant …

Hyperspectral image and videos provide rich spectral information content, which facilitates
accurate classification, unmixing, temporal change detection, and so on. However, with the …

As a cutting-edge technique for denoising and feature extraction, singular spectrum analysis
(SSA) has been applied successfully for feature mining in hyperspectral images (HSI) …