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Optical Engineering

Information theoretic analysis of linear shift-invariant edge-detection operators
Author(s): Bo Jiang; Zia-ur Rahman
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Paper Abstract

Generally, the designs of digital image processing algorithms and image gathering devices remain separate. Consequently, the performance of digital image processing algorithms is evaluated without taking into account the influences by the image gathering process. However, experiments show that the image gathering process has a profound impact on the performance of digital image processing and the quality of the resulting images. Huck et al. proposed one definitive theoretic analysis of visual communication channels, where the different parts, such as image gathering, processing, and display, are assessed in an integrated manner using Shannon's information theory. We perform an end-to-end information theory based system analysis to assess linear shift-invariant edge-detection algorithms. We evaluate the performance of the different algorithms as a function of the characteristics of the scene and the parameters, such as sampling, additive noise etc., that define the image gathering system. The edge-detection algorithm is regarded as having high performance only if the information rate from the scene to the edge image approaches its maximum possible. This goal can be achieved only by jointly optimizing all processes. Our information-theoretic assessment provides a new tool that allows us to compare different linear shift-invariant edge detectors in a common environment.

Paper Details

Date Published: 19 June 2012
PDF: 24 pages
Opt. Eng. 51(6) 067013 doi: 10.1117/1.OE.51.6.067013
Published in: Optical Engineering Volume 51, Issue 6
Show Author Affiliations
Bo Jiang, National Institute of Aerospace (United States)
Zia-ur Rahman, Old Dominion Univ. (United States)


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