Hyperspectral (HS) images contain rich spatial and spectral information. Due to its large
size, it is difficult to store, process, analyze, or transmit the critical information contained in it …

Memory management and coding complexity are the major challenging issues of any
hyperspectral image sensor. The hyperspectral image compression algorithm plays a …

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 …

Memory management of the hyperspectral image sensor is a challenging issue. The existing
hyperspectral image compression schemes play a dominant role in minimizing the cost of …

Hyperspectral (HS) image has rich spectral information content, which facilitates multiple
applications including remote sensing. Due to the big data size of the HS image …

Hyperspectral (HS) image has rich spectral information content, which facilitates multiple
applications including remote sensing. Due to the big data size of the HS image …

Hyper spectral images are image data consisting of hundreds of spectral bands leading to
very large raw data size. Hyper spectral images are usually captured by satellites that use …

Abstract Hyperspectral (HS) images (HSI) provide a vast amount of spatial and spectral
information based on the high dimensionality of the pixels in a wide range of wavelengths. A …

Hyperspectral image resolution offers limited spectral bands within a continual spectral
spectrum, creating one of the spectra of most pixels inside the sequence which contains …

The hyperspectral image provides rich spectral information content, which facilitates multiple
applications. With the rapid advancement of the spatial and spectral resolution of optical …