BAYESIAN IMAGE RESTORATION, USING CONFIGURATIONS
Keywords:Bayesian image analysis, configurations, digital image analysis, salt and pepper noise, stochastic geometry
AbstractIn this paper, we develop a Bayesian procedure for removing noise from images that can be viewed as noisy realisations of random sets in the plane. The procedure utilises recent advances in configuration theory for noise free random sets, where the probabilities of observing the different boundary configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for salt and pepper noise. The inference in the model is discussed in detail for 3 X 3 and 5 X 5 configurations and examples of the performance of the procedure are given.
How to Cite
Thorarinsdottir, T. L. (2011). BAYESIAN IMAGE RESTORATION, USING CONFIGURATIONS. Image Analysis & Stereology, 25(3), 129–143. https://doi.org/10.5566/ias.v25.p129-143
Original Research Paper