Fast search algorithms for digital video coding
Motion Estimation algorithm is one of the important issues in video coding standards such as ISO MPEG-1/2 and ITU-T H.263. These international standards regularly use a conventional Full Search (FS) Algorithm to estimate the motion of pixels between pairs of image blocks. Since a FS method requires intensive computations and the distortion function needs to be evaluated many times for each target block. the process is very time consuming. To alleviate this acute problem, new search algorithms, Orthogonal Logarithmic Search (OLS) and Diagonal Logarithmic Search (DLS), have been designed and implemented. The performance of the algorithms are evaluated by using standard 176x 144 pixels quarter common intermediate format (QCIF) benchmark video sequences and the results are compared to the traditional well-known FS Algorithm and a widely used fast search algorithm called the Three Step Search (3SS), The fast search algorithms are known as sub-optimal algorithms as they test only some of the candidate blocks from the search area and choose a match from a subset of blocks. These algorithms can reduce the computational complexity as they do not examine all candidate blocks and hence are algorithmically faster. However, the quality is generally not as good as that of the FS algorithms but can be acceptable in terms of subjective quality. The important metrics, time and Peak Signal to Noise Ratio are used to evaluate the novel algorithms. The results show that the strength of the algorithms lie in their speed of operation as they are much faster than the FS and 3SS. The performance in speed is improved by 85.37% and 22% over the FS and 3SS respectively for the OLS. For the DLS, the speed advantages are 88.77% and 40% over the FS and 3SS. Furthermore, the accuracy of prediction of OLS and DLS are comparahle to the 3SS.