Paper
7 September 2010 Information theoretic analysis of edge detection in visual communication
Bo Jiang, Zia-ur Rahman
Author Affiliations +
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 artifacts introduced into the process by the image gathering process. However, experiments show that the image gathering process profoundly impacts 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. In this paper, we perform an end-to-end information theory based system analysis to assess edge detection methods. 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 to have high performance only if the information rate from the scene to the edge approaches the maximum possible. This goal can be achieved only by jointly optimizing all processes. People generally use subjective judgment to compare different edge detection methods. There is not a common tool that can be used to evaluate the performance of the different algorithms, and to give people a guide for selecting the best algorithm for a given system or scene. Our information-theoretic assessment becomes this new tool to which allows us to compare the different edge detection operators in a common environment.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bo Jiang and Zia-ur Rahman "Information theoretic analysis of edge detection in visual communication", Proc. SPIE 7799, Mathematics of Data/Image Coding, Compression, and Encryption with Applications XII, 779908 (7 September 2010); https://doi.org/10.1117/12.859928
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Cited by 1 scholarly publication.
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KEYWORDS
Image processing

Edge detection

Digital image processing

Signal to noise ratio

Image quality

Sensors

Visual communications

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