Restoration of Motion-blurred Images Using an Edge Adaptive Kalman Filter

Abstract

This paper presents an edge-adaptive Kalman filter with ringing suppression for restoring motion-blurred images. The ringing artifacts are produced near the edges of images restored by conventional techniques of shift-invariant linear filtering. A one-dimensional non-stationary model is used as an original image, and the degradation model is represented by a uniform, shift-invariant, point-spread function and additive white noise. The image is divided into an edge region and a smooth region. Two Kalman filter gains are designed for these two regions. The image is then restored by the adaptive Kalman filter, which switches the two gains according to edge information. Model parameters and the edge information of the original image are estimated from the image temporarily restored by a deconvolution technique. Finally, computer simulations show that the proposed technique is effective for suppressing the ringing artifacts.