Using kalman filtering methods for image restoration

A common problem in image processing is the restoration of an image from a given corrupted version. This problem is generally known as image restoration. There are various approaches to solve this problem like using restoration models or linear filtering. In this thesis, one of the linear filtering methods named Kalman filtering has been used for image restoration. For this purpose, two different image restoration scenarios have been defined and two different versions of Kalman filtering methods have been used for each of the scenarios. In the first part of the thesis, a simple scalar Kalman filter method is used for an image that contains multiple frames. In the second part of the thesis, a two-dimensional (2-D) full-plane block Kalman filter is used to restore noisy images. Simulation results are compared with some of the other restoration techniques.