Edge Sensitive Block Motion Estimation Employing Partial Ridgelet Distortion Search
Motion estimation is an important field of video processing. Conventional block motion estimation methods consider all pixels equally. In this paper a new edge sensitive algorithm is proposed in which distortion of ridgelet coefficients is calculated partially and compared over all candidates. Using an edge boosting distortion function, edge pixels will have more important role since they introduce larger ridgelet coefficients. Inherent ability of ridgelet in representing edges with various directions in multiscale, makes it a powerful tool for edge pursuit. Proposed partial ridgelet distortion search (PRDS) do not reject any candidate without assessment while performs relatively fast since it operates partially. Experimental results show that the total PSNR of PRDS is near traditional full search while its motion compensated frame has less distortion over edge pixels. It has also less blocking problem, which both are visually annoying effect of traditional methods. Despite larger loser rejection ratio of PRDS, normalized PRDS is also proposed as even faster search with results close to the PRDS