The aim of the paper is to provide an overview of the PRISMA (PRecursore IperSpettrale della Missione Applicativa) mission and the related scientific foreseen applications. The mission development program is in actually in the C phase and it is completely funded by ASI. PRISMA is an earth observation system with innovative electro-optical instrumentation which combines an hyperspectral sensor w...

Compressive hyperspectral imaging is based on the fact that hyperspectral data is highly redundant. However, there is no symmetry between the compressibility of the spatial and spectral domains, and that should be taken into account for optimal compressive hyperspectral imaging system design. Here we present a study of the influence of the ratio between the compression in the spatial and spectr...

We address the two dominant dilemmas encountered in attempting to demonstrate real-time hyperspectral imaging: how to record a three-dimensional spectral data cube with a conventional two-dimensional detector array and how to most efficiently transmit the spectral data cube through the information bottleneck constituted by the detector’s limited space–bandwidth product. We have demonstrated a n...

Hyperspectral image classification has become an important research topic in remote sensing. Because of high dimensional data, a special attention is needed dealing with spectral data; and thus, one of the research topics in hyperspectral image classification is dimension reduction. In this paper, a dimension reduction approach is presented for classification on hyperspectral images. Advantages...

Hyperspectral imaging is a growing area in remote sensing in which an imaging spectrometer collects hundreds of images (at different wavelength channels) for the same area on the surface of the Earth. Hyperspectral images are extremely high-dimensional, and require advanced on-board processing algorithms able to satisfy near real-time constraints in applications such as wildland fire monitoring...

Because of the great data of the hyperspectral image, it is not good for storage and transmission. To work out a high efficiency compression method for hyperspectral image is essential. Prediction encoding is easy to realize and has been studied widely in the hyperspectral image compression field. High compression ratio, resolution independence and fast decoding speed are the main advantages of...

Accurate and in vivo characterization of structural, functional, and molecular characteristics of biological tissue will facilitate quantitative diagnosis, therapeutic guidance, and outcome assessment in many clinical applications, such as wound healing, cancer surgery, and organ transplantation. We introduced and tested a multiview hyperspectral imaging technique for noninvasive topographic im...

Hyperspectral imaging has been widely studied in many applications; notably in climate changes, vegetation, and desert studies. However, such kind of imaging brings a huge amount of data, which requires transmission, processing, and storage resources for both airborne and spaceborne imaging. Compression of hyperspectral data cubes is an effective solution for these problems. Lossless compressio...

We have developed a new and innovative technique for combining a high-spatial-resolution multispectral image with a lower-spatial-resolution hyperspectral image. The approach, called CRISP, compares the spectral information present in the multispectral image to the spectral content in the hyperspectral image and derives a set of equations to approximately transform the multispectral image into ...

Rapid advancement in remote sensing open new avenues to explore the hyperspectral Hyperion imagery pre-processing techniques, analysis and application for land use mapping. The hyperspectral data consists of 242 bands out of which 196 calibrated/useful bands are available for hyperspectral applications. Atmospheric correction applied to the hyperspectral calibrated bands make the data more usef...