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

The 3D-zero memory set partitioned embedded block (3D-ZM-SPECK) is an embedded and
memory-efficient compression algorithm. Through, the 3D-ZM-SPECK does not require any …

Complexity of any onboard hyperspectral image sensor is a challenging issue. The existing
hyperspectral image compression algorithm plays a great role in reducing the data …

Much research is still underway to achieve long-term and real-time monitoring using data
from vision-based sensors. A major challenge is handling and processing enormous amount …

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

The wavelet transform is widely used in the task of hyperspectral image compression
(HSIC). They have achieved outstanding performance in the compression of a hyperspectral …

Compression of remotely sensed astronomical images is an essential part of deep space
exploration. This study proposes a wavelet-based compressed sensing (CS) algorithm for …

Lossless hyperspectral images have the advantage of reducing the data size, hence saving
on storage and transmission costs. This study presents a dynamic pipeline hardware design …

Due to the constrained processing capabilities of real-time detection techniques in remote
sensing applications, it is often difficult to obtain detection results with high accuracy in …

Lossy compression of remote-sensing images is a typical stage in their processing chain. In
design or selection of methods for lossy compression, it is commonly assumed that images …