Fast and Efficient Search Algorithm of Block Motion Estimation

Among the previous searching methods, there are the typical methods such as full search and three-step search, etc. Block motion estimation using exhaustive search is too computationally intensive. To apply in practice, recently proposed fast algorithms have been focused on reducing the computational complexity by limiting the number of searching points. According to the reduction of searching points, the quality performance is aggravated in those algorithms. In this paper, We present a fast and efficient search algorithm for block motion estimation that produces better quality performance and less computational time compared with a three-step search (TSS). Previously the proposed Two Step Search Algorithm (TWSS) by Fang-Hsuan Cheng and San-Nan sun is based on the ideas of dithering pattern for pixel decimation using a part of a block pixels for BMA (Block Matching Algorithm) and multi-candidate to compensate quality performance with several locations. This method has good quality performance at slow moving images, but has bad quality performance at fast moving images. To resolve this problem, the proposed algorithm in this paper considers spatial and temporal correlation using neighbor and previous blocks to improve quality performance. This performance uses neighbor motion vectors and previous motion vectors in addition, thus it needs more searching points. To compensate this weakness, the proposed algorithm uses statistical character of dithering matrix. The proposed algorithm is superior to TWSS in quality performance and has similar computational complexity