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 on-board processing algorithms able to satisfy near real-time constraints in applications such as wildland fire monitoring, mapping...

This paper presents a real-time target detection architecture for hyperspectral image processing. The architecture is based on a reduced complexity algorithm for high-throughput applications.We propose an efficient pipelined processing element architecture and a scalable multiple-processing element architecture by exploiting data partitioning. We present a processing unit modeling based on the ...

Classification of heterogeneous classes present in the Hyperspectral image is one of the recent research issues in the field of remote sensing. This work presents a novel technique that classifies Hyperspectral images that contain number of classes by making use of the image moments. Recently, researchers have introduced a number of neural network models and structured output based methods for ...

Hyperspectral image compression has received considerable interest in recent years due to the enormous data volumes collected by imaging spectrometers for Earth Observation. JPEG2000 is an important technique for data compression, which has been successfully used in the context of hyperspectral image compression, either in lossless and lossy fashion. Due to the increasing spatial, spectral, and...

In this paper, we discuss about hyperspectral image processing where it plays an important role in remote sensing, hyperspectral verses multispectral image processing and image classifications. Where these classifications includes image sensors, image preprocessing, object detection, object segmentation, feature extraction and object classification. Mainly there are two types of classifications...

This paper outlines the design and implementation of Grid-HSI, a Service Oriented Architecturebased Grid application to enable hyperspectral imaging analysis. Grid-HSI provides users with a transparent interface to access computational resources and perform remotely hyperspectral imaging analysis through a set of Grid services. Keyword: Grid computing, portal grid, remote sensing, image process...

This paper describes the development of a signal and image processing system for the Hyperspectral Biomedical Imager (HBI). The HBI forms hyperspectral images of human tissue with high spatial and spectral resolution. The final goal of the research project is to develop a fully functional HBI image formation/processing system based on the TMS320C6X. This would permit fast and efficient data pro...

Imaging spectroscopy, also known as hyperspectral imaging, is a new technique that has gained tremendous popularity in many research areas, including satellite imaging and aerial reconnaissance. In particular, NASA is continuously gathering high-dimensional image data from the surface of the earthwith hyperspectral sensors such as the Jet Propulsion Laboratory’s Airborne Visible-Infrared Imagin...

Hyperspectral imaging is a new technique in remote sensing that generates hundreds of images, at different wavelength channels, for the same area on the surface of the Earth. In recent years, several efforts have been directed towards the incorporation of high-performance computing systems and architectures into remote sensing missions. With the aim of providing an overview of current and new t...

This paper covers 60 years of terrestrial imaging spectroscopy or hyperspectral remote sensing – 30 years each devoted to past and future developments. For this purpose, a brief history of imaging spectroscopy is given, covering civilian airborne sensor and spaceborne mission developments and associated data processing capabilities. Moreover, the paper reviews the existing and planned space sys...