Video deblurring and super-resolution technique for multiple moving objects

Video camera is now commonly used and demand of capturing a single frame from video sequence is increasing. Since resolution of video camera is usually lower than digital camera and video data usually contains a many motion blur in the sequence, simple frame capture can produce only low quality image; image restoration technique is inevitably required. In this paper, we propose a method to restore a sharp and high-resolution image from a video sequence by motion deblur for each frame followed by super-resolution technique. Since the frame-rate of the video camera is high and variance of feature appearance in successive frames and motion of feature points are usually small, we can still estimate scene geometries from video data with blur. Therefore, by using such geometric information, we first apply motion deblur for each frame, and then, super-resolve the images from the deblurred image set. For better result, we also propose an adaptive super-resolution technique considering different defocus blur effects dependent on depth. Experimental results are shown to prove the strength of our method.