Resolution enhancement of monochrome and color video using motion compensation

In this paper, we propose an iterative algorithm for enhancing the resoluti on of monochrome and color image sequences. Various approaches toward motio n estimation are investigated and compared. Improving the spatial resolutio n of an image sequence critically depends upon the accuracy of the motion e stimator. The problem is complicated by the fact that the motion field is p rone to significant errors since the original high-resolution images are no t available. Improved motion estimates may be obtained by using a more robu st and accurate motion estimator, such as a pel-recursive scheme instead of block matching. In processing color image sequences, there is the added ad vantage of having more flexibility in how the final motion estimates are ob tained, and further improvement in the accuracy of the motion field is ther efore possible. This is because there are three different intensity fields (channels) conveying the same motion information. In this paper, the choice of which motion estimator to use versus how the final estimates are obtain ed is,weighed to see which issue is more critical in improving the estimate d high-resolution sequences, Toward this end, an iterative algorithm is pro posed, and two sets of experiments are presented. First, several different experiments using the same motion estimator but three different data fusion approaches to merge the individual motion fields were performed. Second, e stimated high-resolution images using the block matching estimator were com pared to those obtained by employing a pel recursive scheme, Experiments we re performed on a real color image sequence, and performance was measured b y the peak signal to noise ratio (PSNR).