1 May 1999 Information-theoretic assessment of sampled imaging systems
Friedrich O. Huck, Carl L. Fales, Rachel Alter-Gartenberg, Stephen K. Park, Zia-ur Rahman
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By rigorously extending modern communication theory to the assessment of sampled imaging systems, we develop the formulations that are required to optimize the performance of these systems within the critical constraints of image gathering, data transmission, and image display. The goal of this optimization is to produce images with the best possible visual quality for the wide range of statistical properties of the radiance field of natural scenes that one normally encounters. Extensive computational results are presented to assess the performance of sampled imaging systems in terms of information rate, theoretical minimum data rate, and fidelity. Comparisons of this assessment with perceptual and measurable performance demonstrate that (1) the information rate that a sampled imaging system conveys from the captured radiance field to the observer is closely correlated with the fidelity, sharpness and clarity with which the observed images can be restored and (2) the associated theoretical minimum data rate is closely correlated with the lowest data rate with which the acquired signal can be encoded for efficient transmission.
Friedrich O. Huck, Carl L. Fales, Rachel Alter-Gartenberg, Stephen K. Park, and Zia-ur Rahman "Information-theoretic assessment of sampled imaging systems," Optical Engineering 38(5), (1 May 1999). https://doi.org/10.1117/1.602264
Published: 1 May 1999
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Cited by 35 scholarly publications.
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KEYWORDS
Imaging systems

Quantization

Image restoration

Visualization

Image processing

Image quality

Interference (communication)

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