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

With advantages such as non-destructiveness, high sensitivity and high accuracy, optical
techniques have successfully integrated into various important physical quantities in …

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

Real-time hyperspectral imaging on-board compression represents a critical processing
step in many remote sensing applications where the acquired hyperspectral data need to be …

The computerization of images have been important for different medical applications.
Nevertheless, the huge volume of medical images can rapidly saturate transmission …

With the development of remote sensing technology, spatial and spectral resolutions of
hyperspectral images have become increasingly dense. In order to overcome difficulties in …

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 …

The release of the CUDA Kepler architecture in March 2012 has provided Nvidia GPUs with
a larger register memory space and instructions for the communication of registers among …

The fast compression of images is a requisite in many applications like TV production,
teleconferencing, or digital cinema. Many of the algorithms employed in current image …

Image coding systems have been traditionally tailored for multiple instruction, multiple data
(MIMD) computing. In general, they partition the (transformed) image in codeblocks that can …