FAST TRACK COMMUNICATION Hyperparameter estimation in image restoration

The hyperparameter in image restoration by the Bayes formula is an important quantity. This communication shows a physical method for the estimation of the hyperparameter without approximation. For artificially generated images by prior probability, the hyperparameter is computed accurately. For practical images, accuracy of the estimated hyperparameter depends on the magnetization and energy of the images. We discuss the validity of prior probability for an original image. PACS numbers: 02.50.−r, 05.50.+q, 07.05.Pj, 95.75.Mn Mathematical methods in statistical physics have been applied to information processing problems [1]. A probabilistic model has been used to construct the problems. An analogy between a probabilistic model and a formula of statistical physics supports the validity for applicability. One of the main topics which deals with statistical-physics approaches to information processing problems is image restoration [2]. An image on a computer is represented by a sequence of bits. When a digital image is transferred through a channel, it i