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Proceedings Paper

Information theoretical assessment of digital imaging systems
Author(s): Sarah John; Zia-ur Rahman; Friedrich O. Huck; Stephen E. Reichenbach
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Paper Abstract

The end-to-end performance of image gathering, coding, and restoration as a whole is considered. This approach is based on the pivotal relationship that exists between the spectral information density of the transmitted signal and the restorability of images from this signal. The information-theoretical assessment accounts for (1) the information density and efficiency of the acquired signal as a function of the image-gathering system design and the radiance-field statistics, and (2) the improvement in information efficiency and data compression that can be gained by combining image gathering with coding to reduce the signal redundancy and irrelevancy. It is concluded that images can be restored with better quality and from fewer data as the information efficiency of the data is increased. The restoration correctly explains the image gathering and coding processes and effectively suppresses the image-display degradations.

Paper Details

Date Published: 1 October 1990
PDF: 14 pages
Proc. SPIE 1309, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing, (1 October 1990); doi: 10.1117/12.21758
Show Author Affiliations
Sarah John, Science and Technology Corp. (United States)
Zia-ur Rahman, Science and Technology Corp. (United States)
Friedrich O. Huck, NASA/Langley Research Ctr. (United States)
Stephen E. Reichenbach, Univ. of Nebraska (United States)


Published in SPIE Proceedings Vol. 1309:
Infrared Imaging Systems: Design, Analysis, Modeling, and Testing

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