Search Algorithm For Motion Estimation Research Articles

A complexity-bounded motion estimation algorithm

The full search motion estimation algorithm for video coding is a procedure of high computational cost. For this reason, in real-time low-power applications, low-cost motion estimation algorithms are viable solutions. A novel reduced complexity motion estimation algorithm is presented. It conjugates the reduction of computational load with good encoding efficiency. It exploits the past history of the motion field to predict the current motion field. A successive refinement phase gives the final motion field. This approach leads to a sensible reduction in the number of motion vector that have to be tested. The complexity is lower than any other algorithm algorithms known to the authors, in the literature, it is constant as there is no recursivity in the algorithm and independent of any search window area size. Experimental evaluations have shown the robustness of the algorithm when applied on a wide set of video sequences--a good performance compared to other reduced complexity algorithms and negligible loss of efficiency versus the full search algorithm.

A fast full search motion estimation algorithm using sequential rejection of candidates from hierarchical decision structure

We propose a new as well as fast full search (FS) motion estimation algorithm for video coding. The computational reduction comes from sequential rejection of impossible candidates with derived formula and subblock norms. Our algorithm reduces more the computations than the FS motion estimation algorithms previously developed.

An improved search algorithm for motion estimation using adaptive search order

An adaptive search order (ASO) algorithm is presented to speed up the block motion estimation in digital video coding. According to the motion trend, a table of the adaptive search order is defined. For each searching iteration, a better search order is derived and then the best matched block can be found in the early search stage. Some experimental results demonstrate the computational advantage of the proposed improved algorithm when compared to previous algorithms, such as the full search algorithm, the successive elimination algorithm, the block sum pyramid algorithm, and the multilevel successive elimination algorithm.

A center-biased adaptive search algorithm for block motion estimation

A number of sub-optimal, but faster, search algorithms have been proposed in the literature, in order to alleviate the complexity associated with motion estimation by the full-search method. A new sub-optimal center-biased adaptive search algorithm for motion estimation is proposed; we refer to this algorithm as center-biased dynamic MInima Bounded Area Search (MIBAS) algorithm. The novelty of MIBAS is the checking point pattern at each subsequent step, composed of points lying in the area bounded by two local minima found at the present step, rather than points lying in a small neighborhood around a local minimum. The simulation results show that, compared to other fast algorithms, the center-biased MIBAS is more robust and produces smaller prediction errors and more reliable motion vectors, while it has a comparable computational complexity.

Mapping real-time motion estimation type algorithms to memory efficient, programmable multi-processor architectures

In this paper, an architectural template is presented, which is able to execute the full search motion estimation algorithm or other similar video or image processing algorithms in real time. The architecture is based on a set of programmable video signal processors (VSP's). It is also possible to integrate the processor cores and their local memories on a (set of) chip(s). Due to the programmability, the system is very flexible and can be used for emulation of other similar block-oriented local-neighborhood algorithms. The architecture can be easily divided into several partitions, without data-exchange between partitions. Special attention is paid to memory size and transfer optimization, which are dominant factors for both area and power cost. The trade-offs and techniques used to arrive at these solutions are explained in detail. It is shown that careful optimizations can lead to large savings in memory size (up to 66%) and bandwidth requirements (up to a factor of 4) compared to a straightforward solution.

Successive elimination algorithm for motion estimation

The correspondence presents a fast exhaustive search algorithm for motion estimation. The basic idea is to obtain the best estimate of the motion vectors by successively eliminating the search positions in the search window and thus decreasing the number of matching evaluations that require very intensive computations. Simulation results demonstrate that although the performance of the proposed algorithm is the same as that using the exhaustive search, the computation time has been reduced significantly.

One-dimensional full search motion estimation algorithm for video coding

A new hardware-oriented algorithm called the one-dimensional full search (1DFS) is presented for block-matching motion estimation in video compression. The simulation for this algorithm follows H.261 and MPEG international standards. In MPEG simulation, structures with 1-, 2- and 3-frame interpolation are compared. The performance of 1DFS is superior to that of other fast search algorithms. And it has more regular data flow, data reuse and less control overhead. It is an alternative for 2D full search block matching and achieves a good compromise between computational complexity and performance. With competent performance and reasonable computation complexity, the proposed method is more suitable for real-time hardware realization of a VLSI motion estimator for video applications. >