Due to the nature of mulitspectral images, it is difficult to present all available information in a single image. This study addresses the need for data compression, to enable faster and easier evaluation of a subject containing important details in a wide spectral range. The specific aim of this research is to construct algorithms to in effect compress sampled wide-band electromagnetic data into the visible range. This will present maximum image details within a final color image. The developed compression scheme aims to achieve the high efficiency while keeping the best quality of image subjects. Ancient documents (from the Dead Sea Scrolls) were used as test subjects because certain regions of the document contain important characters detectable only in the infrared region of the spectrum, while other characters are only in ultraviolet. Algorithms for translation, flat fielding, interpolation, incorporation of human response curves and scaling were among those used. The theory and application of this algorithm to multispectral images will be presented.
Gypson, Matthew, "Rendering multispectral data as useful 'Super-Visual' images" (2000). Thesis. Rochester Institute of Technology. Accessed from
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