A Mixture-site Model for Edge-preserving Image Restoration
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چکیده
This paper summarizes a new Bayesian method for edge-preserving image restoration from noisy measurements. The line-site method of Geman and Geman forces region boundaries to lie along pixel boundaries, which is unnatural, particularly for 3D data. Here, we augment the intensity process with a binary “mixture site” process, which has one parameter for each pixel indicating the presence of a boundary a some unknown location within that pixel. The method was motivated by PET and SPECT transmission images with partial volume effects, and is easily extended to 3D data sets.
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A Mixture-Site Model for Edge-Preserving Image Restoration
This paper summarizes a new Bayesian method for edge-preserving image restoration from noisy measurements. The line-site method of Geman and Geman forces region boundaries to lie along pixel boundaries, which is unnatural, particularly for 3D data. Here, we augment the intensity process with a binary \mixture site" process, which has one parameter for each pixel indicating the presence of a bou...
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