INTRODUCTION Hyperspectral imaging has been used in dermatology for many years. The enrichment of hyperspectral imaging with image analysis broadens considerably the possibility of reproducible, quantitative evaluation of, for example, melanin and haemoglobin at any location in the patient's skin. The dedicated image analysis method proposed by the authors enables to automatically perform this ...

Near-infrared chemical imaging (NIR-CI) is the fusion of near-infrared spectroscopy and image analysis. It can be used to visualize the spatial distribution of the chemical compounds in a sample (providing a chemical image). Each sample measurement generates a hyperspectral data cube containing thousands of spectra. An important part of a NIR-CI analysis is the data processing of the hyperspect...

We propose a specific content-based image retrieval (CBIR) system for hyperspectral images exploiting its rich spectral information. The CBIR image features are the endmember signatures obtained from the image data by endmember induction algorithms (EIAs). Endmembers correspond to the elementary materials in the scene, so that the pixel spectra can be decomposed into a linear combination of end...

Since hyperspectral imagery is generated by collecting hundreds of contiguous bands, uncompressed hyperspectral imagery can be very large, with a single image potentially occupying hundreds of megabytes. For instance, the Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) sensor is capable of collecting several gigabytes of data per day. Compression is thus necessary to facilitate both the...

■ This article presents an overview of the theoretical and practical issues associated with the development, analysis, and application of detection algorithms to exploit hyperspectral imaging data. We focus on techniques that exploit spectral information exclusively to make decisions regarding the type of each pixel—target or nontarget—on a pixel-by-pixel basis in an image. First we describe th...

Hyperspectral images (HSI) have the advantage of high spectral resolution and permit discriminate between different compounds. We confront the situation that we obtain many data for an image, this problem suggest the idea of data reduction as band subset selection (BSS). The Laboratory of Applied Remote Sensing and Image Processing (LARSIP) has develop algorithms for classification system and b...

Hyperspectral images have the high spectral resolution rather than to multispectral images. By development of remote sensing technology, the new sensors with hyperspectral capabilities in RS science will be replaced to multispectral imaging. A big advantage of hyperspectral images comparison to that of multispectral images is a continuous spectrum for each image cell that can be derived from im...

Air-borne and space-borne acquired hyperspectral images are used to recognize objects and to classify materials on the surface of the earth. The state of the art compressor for lossless compression of hyperspectral images is the Spectral oriented Least SQuares (SLSQ) compressor (see [1–7]). In this paper we discuss hyperspectral image compression: we show how to visualize each band of a hypersp...