Hyperspectral image classification can be achieved by modeling an energy minimization problem on a graph of image pixels. In this paper, an effective spectral-spatial classification method for hyperspectral images based on joint bilateral filtering (JBF) and graph cut segmentation is proposed. In this method, a novel technique for labeling regions obtained by the spectral-spatial segmentation p...

Remotely-sensed images of the earth’s surface are used across a wide range of industries and applications including agriculture, mining, defence, geography and geology, to name but a few. Hyperspectral sensors produce these images by providing reflectance data from the earth’s surface over a broad range of wavelengths or bands. Some of the bands suffer from a low signal-tonoise ratio (SNR) and ...

Hyperspectral images have been used in anomaly and change detection applications such as search and rescue operations where it is critical to have fast detection. However, conventional Reed-Xiaoli (RX) algorithm [6] took about 600 seconds using a PC to finish the processing of an 800x1024 hyperspectral image with 10 bands. This is not acceptable for real-time applications. A more recent algorit...

Hyperspectral sensors acquire images with hundreds of spectral channels. These images have a lot of information in both spectral and spatial domain, and with this kind of information different research studies can be accomplished. In this work, we present several optimizations for hyperspectral image processing algorithms intended to detect targets in hyperspectral images. The hyperspectral ima...

There is great interest in the development of automatic geometric correction systems for satellite images. A fully automatic system, based exclusively on the identification of tie points (image to image control points) by image matching needs to use efficient selection and validation methods. Four Tie Point Suitability Indices (TPSI) are proposed to select the most suitable areas in an image to...

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...

Recently, real-time image data processing is a popular research area for hyperspectral remote sensing. In particular, target detection surveillance, which is an important military application of hyperspectral remote sensing, demands real-time or near real-time processing. The massive amount of hyperspectral image data seriously limits the processing speed. In this article, a strategy named spat...

Hyperspectral cameras preserve the fine spectral details of scenes that are generally lost in the traditional RGB cameras due to the gross quantization of radiance. These details are desirable in numerous imaging applications, nevertheless the high cost of hyperspectral hardware and the associated physical constraints currently limit the pervasive use of hyperspectral imaging. We take a computa...