Nowadays, video camera is commonly used everywhere and demand of retrieving a single shot from video sequence is increasing. Since resolution of video camera is usually lower than that of digital camera, simply cutting out a frame from a video sequence ends up with low quality. Further, because of the necessity of high fps on video camera, video data inevitably contains motion blur and it leads mis-registration between frames which is critical for multi-frame superresolution. In this paper, we propose a method to restore high-resolution image from a video sequence considering motion blur. Since the frame-rate of a video camera is high, motion of the object in successive frames is small, and thus, stable feature tracking during short sequences is possible even if there is a blur. Thus, we adopt a division/integration approach to realize robust tracking for long sequence. We also propose a simultaneous deblur and super-resolution technique using multiple images based on MAP estimation. Experimental results are shown to prove the strength of our method.