Abstract
Block matching motion estimation was one of the most important modules in the design of any video encoder. It consumed more than 85% of video encoding time due to searching of a candidate block in the search window of the reference frame. To minimize the search time on block matching, a simplified and efficient Block Matching Algorithm for Fast Motion Estimation was proposed. It had two steps such as prediction and refinement. The temporal correlation among successive frames and the direction of the previously processed frame for predicting the motion vector of the candidate block was considered during prediction step. Different combination of search points was considered in the refinement step of the algorithm which subsequently minimize the search time. Experiments were conducted on various SIF and CIF video sequences. The performance of the algorithm was compared with existing fast block matching motion estimation algorithms which were used in recent video coding standards. The experimental results were shown that the algorithm provided a faster search with minimum distortion when compared to the optimal fast block matching motion estimation algorithms.
Highlights
Block-matching motion estimation is the most important module for any motion compensated video coding standards such as ISO/IEC MPEG[1] and ITUT[2]
An assumption is made on the maximum distance; objects in the video sequence tend to move between adjacent frames
The experiments were conducted on three SIF (Source Input Format) video sequences such as Bike, (352×240, 147 frames, 30 fps, 24 bpp), Flower Garden (352×240, 147 frames, 30 fps, 24bpp), Table Tennis, (352×240, 147 frames, 30 fps, 24 bpp) and a CIF (Common Intermediate Format) Football, (352×288, 50 frames, 25 fps, 24 bpp) video sequence
Summary
Block-matching motion estimation is the most important module for any motion compensated video coding standards such as ISO/IEC MPEG[1] and ITUT[2]. The block-matching algorithms eliminate the temporal redundancy, which is found predominantly in any video sequence. It divides frames into equal sized non-overlapping blocks and calculates the displacement of the best-matched block from the previous frame as the motion vector of the block in the current frame within the search window. Each target block of the current frame is compared with a previous frame in order to find the best matching block. Block-matching algorithms calculate the best match using Mean Absolute Difference (MAD)[3]. The Full search algorithm provides the best result by matching all possible blocks within the search window. It lacks significantly in computation time, which necessitates improvement
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