Abstract
Numerous fast-search block motion estimation algorithms have been developed to circumvent the high computational cost required by the full-search algorithm. These techniques however often converge to a local minimum, which makes them subject to noise and matching errors. Hence, many spatial domain block matching algorithms have been developed in literature. These algorithms exploit the high correlation that exists between pixels inside each frame block. However, with the block transformed frequencies, block matching can be used to test the similarities between a subset of selected frequencies that correctly identify each block uniquely; therefore fewer comparisons are performed resulting in a considerable reduction in complexity. In this work, a two-level hierarchical fast search motion estimation algorithm is proposed in the frequency domain. This algorithm incorporates a novel search pattern at the top level of the hierarchy. The proposed hierarchical method for motion estimation not only produces consistent motion vectors within each large object, but also accurately estimates the motion of small objects with a substantial reduction in complexity when compared to other benchmark algorithms.
Highlights
A moving video frame is captured by taking a rectangular snapshot of the natural signal at periodic time intervals
Different criteria should be investigated such as the well-known Mean Square Error (MSE), the Mean Absolute Difference (MAD), and the Sum of Absolute Difference (SAD)
13 standard Quarter Common Intermediate File (QCIF) and Common Intermediate File (CIF) video sequences of different motion contents are used to compare the performance of different algorithms
Summary
A moving video frame (image) is captured by taking a rectangular snapshot of the natural signal at periodic time intervals. In inter-frame coding, motion estimation and compensation (two vital processes within video coding) have become powerful techniques to eliminate the temporal redundancy due to high correlation between consecutive frames. BMAs are more suitable for a simple hardware realization because of their regularity and simplicity They estimate motion on the basis of rectangular blocks and produce one motion vector for each block. The motion vector and the resulting error can be transmitted instead of the original luminance block; inter-frame redundancy is removed and data compression is achieved. High correlation exists between pixels inside each frame block; the general block matching usually require measuring the similarities between every pair of pixels inside each block. The algorithm uses the intracoded frequency domain transformed frame in order to perform the proposed block matching technique.
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