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Variational Bayesian Inference Based Image Inpainting using Gamma Distribution Prior
Rohit Sain,Vikas Mittal,Vrinda Gupta 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.12
Variational Bayesian (VB) inference is the latest iterative method for prediction of data in machine learning. It provides the solution for intractable integration in Bayesian methodology. In this paper, a simple VB linear regression is applied for prediction of the damaged pixels in an image. Bayesian linear regression model is used for prediction of the pixels. For this neighbor pixels are used as training data to generate the parameters of the prediction function. Now using this prediction function, damaged pixels are predicted and incorporated into the image. Proposed method is linear while image is a non-linear object, generally. Hence, for linearity, a small image window size is used to avoid the nonlinearities in image.