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Image segmentation based on the multiresolution Fourier transform and Markov random fields
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Chen, Guo-Huei and Wilson, Roland (1999) Image segmentation based on the multiresolution Fourier transform and Markov random fields. University of Warwick. Department of Computer Science. (Department of Computer Science research report). (Unpublished)
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PDF (Department of Computer Science Research Report)
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Abstract
In this work, the Multiresolution Fourier Transform (MFT) and Markov Random Fields (MRFs) are combined to produce as a tool for image segmentation. Firstly, a Laplacian Pyramid is used as a high-pass filter. Then, the MFT is applied in order to segment images based on the analysis of local properties in the spatial frequency domain. A methodology for edge detection in image segmentation in the Bayesian framework using Markov random field models is then developed. Stochastic Relaxation is also adopted to maximise the likelihood and find the globally minimum energy states using simulated annealing.
Item Type: | Report | ||||
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Subjects: | T Technology > TA Engineering (General). Civil engineering (General) | ||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||
Library of Congress Subject Headings (LCSH): | Image segmentation, Markov random fields, Fourier transformations | ||||
Series Name: | Department of Computer Science research report | ||||
Publisher: | University of Warwick. Department of Computer Science | ||||
Official Date: | 21 September 1999 | ||||
Dates: |
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Number: | Number 351 | ||||
Number of Pages: | 23 | ||||
DOI: | CS-RR-351 | ||||
Institution: | University of Warwick | ||||
Theses Department: | Department of Computer Science | ||||
Status: | Not Peer Reviewed | ||||
Publication Status: | Unpublished | ||||
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