Rapid and continuous advancements in remote sensing technology have resulted in finer
resolutions and higher acquisition rates of hyperspectral images (HSIs). These …

Hyperspectral compressed sensing (HCS) is a new imaging method that effectively reduces
the power consumption of data acquisition. In this article, we present a novel HCS algorithm …

Sparse unmixing (SU) algorithms use the existing spectral library as prior knowledge to
analyze the endmembers and estimate abundance maps. The majority of SU algorithms use …

Rapid advancements in hyperspectral (HS) methodologies for image analysis have resulted
in specialized HS tasks, well-known for their extensive spatial-spectral data. Spectral bands …

The information society has higher and higher requirements for the collection, transmission
and storage of digital signals, and signal utilization efficiency has become an increasingly …

Hyperspectral polarized images are widely used in target detection, and compressive
sensing has been developed to shorten the acquisition time and reduce the memory usage …

Nowadays, microscopy images are significant in medical research and clinical studies.
However, storage and transmission of data such as microscopy images are challenging …

The ever-increasing resolution puts tremendous pressure to the onboard hyperspectral
imaging system. Compressed sensing technology is one of the important ways to solve this …

The outstanding spectral resolution of full-spectrum detection (FSD) ensures excellent
performance for complex scenarios in which target signals are affected by particle …

Compressed sensing (CS), as an efficient data transmission method, has achieved great
success in the field of data transmission such as image, video and text. It can robustly …