KEYWORDS: Video, Motion estimation, Detection and tracking algorithms, Video coding, Standards development, Distortion, Video compression, Computer programming, Image compression, Signal to noise ratio
The paper presents a novel Orthogonal Logarithmic Search (OLS) method for block base motion compensation. The performance of the algorithm is evaluated by using standard QCIF benchmark video sequences and the results are compared to a traditional well-known full search algorithm (FSA) and a sub-optimal method called the Three Step Search (3SS). The evaluation considers the three important metrics, time, entropy and PSNR (Peak Signal to Noise Ratio). The paper also shows that the strength of the algorithm lies in its speed of operation as it is 95% faster than the FSA and over 60% faster than the 3SS.
Investigation into motion estimation algorithms is one of the important issues in the video coding standards such as ISO MPEG-1/2 and ITU-T H.263. These international standards regularly use a conventional FSA to estimate the motion of pixels between pairs of image block matching algorithms. Since a full search requires intensive computations and the distortion function needs to be evaluated many times for each target block to be matched, the process is very time consuming. Therefore, the main aim of this investigation has been to alleviate this acute problem of search speed and accuracy.
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