Contre-examples for Bayesian MAP restoration
نویسنده
چکیده
The Bayesian approach is most widely used to solve various problems in signal and image processing, such as denoising and deblurring, zooming, reconstruction. The reason is that it provides a coherent statistical framework to combine observed (noisy) data with prior information on the unknown signal or image. However, this paper exhibits a major contradiction since the MAP solutions substantially deviate from both the data-acquisition model and the prior model. This is illustrated using experiments and explained based on some known analytical properties of the MAP solutions.
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