Paper
21 February 2013 Discussion on information theoretic and simulation analysis of linear shift-invariant edge detection operators
Author Affiliations +
Proceedings Volume 8666, Visual Information Processing and Communication IV; 866602 (2013) https://doi.org/10.1117/12.2001524
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States
Abstract
Generally, the designs of digital image processing algorithms and image gathering devices remain separate. However, experiments show that the image gathering process profoundly impacts the performance of digital image processing and the quality of the resulting images. We proposed an end-to-end information theory based system to assess linear shift-invariant edge detection algorithms, where the different parts, such as scene, image gathering, and processing, are assessed in an integrated manner using Shannon’s information theory. We evaluated 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. To validate our information theoretical conclusions, a series of experiments simulated the whole image acquisition process are conducted. After comparison and discussion between theoretic analysis and simulation analysis, we can draw a conclusion that the proposed information-theoretic assessment provides a new tool which allows us to compare different linear shift-invariant edge detectors in a common environment.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bo Jiang "Discussion on information theoretic and simulation analysis of linear shift-invariant edge detection operators", Proc. SPIE 8666, Visual Information Processing and Communication IV, 866602 (21 February 2013); https://doi.org/10.1117/12.2001524
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KEYWORDS
Signal to noise ratio

Image processing

Edge detection

Sensors

Digital image processing

Image quality

Detection and tracking algorithms

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