On edge preservation in multiresolution images |
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| Affiliation: | 1. Center for Artificial Intelligence, University of Technology Sydney, Australia;2. College of Computer Science and Technology, Wuhan University of Science and Technology, China;3. Chongqing Key Laboratory of Signal and Information Processing, Chongqing University of Posts and Telecommunications, China;1. Department of Computer Science and Technology, Huazhong University of Science and Technology, Luoyu Road 1037, Wuhan, China;2. School of EEECS Computer Science Building, Queen’s University, UK |
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| Abstract: | Multiresolution image processing and analysis has become popular in recent years. One of the most important factors for the success of such systems is the preservation of edges in the process of producing images with reduced resolutions. In this paper 10 image reduction methods are introduced and a comparative evaluation is presented by using a set of synthetic test images and several real images. The quantitative evaluation employs an error measure based on normalized mean-square errors and a set of well-defined image parameters. Edge separation parameter is found to have a strikingly decisive impact on the edge preservation in the context of image reduction. Noise and edge width also show their significant effects. A normalized local intensity variance is studied to bridge the gap between the simple synthetic images and the real images. Finally, suitable methods for producing multiresolution images are recommended. |
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