Traditional Block Matching Algorithm Research Articles

A Novel Frame Rate Up-Conversion Algorithm Based on Soft Threshold Bandelet Transform

The most important part of frame rate up-conversion (FRUC) is block matching. The geometric properties of the image were not taken into consideration in traditional block matching algorithm, so the matching result of motion estimation cannot reach the optimal. A novel FRUC algorithm based on Bandelet was proposed in this paper. The algorithm includes: Firstly, a soft threshold Bandelet transform of matching block was performed. The optimal matching block was determined through detection of direction similarity and Bandelet coefficient similarity; secondly, vector median filtering (VMF) and overlapped block motion compensation (OBMC) were carried out by adopting motion vector to realize interpolated frame algorithm. Experimental results show that the FRUC algorithm based on Bandelet can further promote the quality of FRUC.

Motion Estimation Based on Adaptive Kalman Filter and Its Application in Video Coding

Most of the traditional block-matching algorithms for motion estimation (ME) can only yield local optimal motion vectors (MVs). In this paper, the autoregressive moving average process (ARMA) model is selected to formulate the correlation of neighboring blocks in a frame, and the adaptive Kalman filtering algorithm is applied to refine the MVs. The horizontal and vertical ARMA models are constructed to utilize the filtering algorithm twice to get a better performance. Our method can also be extended to realize disparity estimation (DE) in order to apply it in a multi-view video coding (MVC) system. The experiment results show the effectiveness of our method to improve the accuracy of conventional fast block matching algorithms.

Motion Estimation Algorithms Using the Deformation of Planar Hierarchical Mesh Grid for Videoconferencing Applications at Low Bit-rate Transmission

This paper studies the issue of reducing the temporal redundancy between consecutive frames of a videoconferencing sequence at low bit-rate transmission. To overcome the drawbacks of the traditional block matching algorithm implemented in the most current video coding standards, we propose to better describe the motion of objects through the deformation of planar rectangular mesh grid adapted to the edges of the moving objects in the scene. The traditional inter coding modes are then replaced by two new classes of encoding algorithms. The first one concerns the B-frames where the problem of motion estimation is solved by a bidirectional prediction algorithm which reconstructs the quadrilateral mesh grids without any coding cost. The second class of algorithm much more complex than the first one is specific to the P-frames based on the principle of merging two hierarchical grids of reference. This algorithm addresses not only the motion estimation problem based on the adaptive quadrilateral mesh grid but also the issue of the relevant information (e.g. the positions of the nodes, the connectivity of each quadrilateral mesh of the grid and the motion compensation) to efficiently encode. The implementation of these algorithms in a complete coding scheme offers good performance compared to the H.264/AVC video coder at low bit-rate transmission.

Enhanced Block Motion Estimation Based on Threshold-Aware Two-Path Search Method

For stationary or quasi-stationary frames of a video sequence, traditional block matching algorithms (BMA) will easily lead the search to be trapped into a local minimum. In this paper, a novel method called the threshold-aware two-path search (TATPS) block matching algorithm is presented. Different from other BMAs, our proposed TATPS algorithm uses two search paths. With the threshold predetermined by the ratio of block distortion measure (BMD), when the value of the observed indicator in the first search step is greater than this threshold, another search path is enabled. Our approach is to compensate the performance degradation due to insufficient number of candidate blocks in traditional BMAs. Experimental results show that the proposed TATPS algorithm can get better performance than the traditional BMAs while just increasing little computational cost.

New kernels for fast mesh-based motion estimation

Mesh-based motion estimation-also known as control grid interpolation or warping-provides a smoother estimated intensity field compared to the traditional block-matching algorithm (BMA), resulting in most cases in a more realistic motion field and smaller estimation error. In mesh-based motion, unlike BMA, the computation of a motion vector is affected by its neighboring vectors. This interdependence necessitates a costly, iterative computation of motion vectors. The computational cost of mesh-based motion has been a main drawback of this otherwise powerful technique. We propose to use noniteratively computed motion vectors, such as BMA motion vectors, for node motions in the mesh model. However, we found that a straightforward insertion of BMA motion vectors in the deformable mesh leads to unpredictable and erratic results, and were thus motivated to carefully analyze the interaction of motion vectors and interpolation kernels in mesh models. This analysis leads to a methodology for computing optimal motion interpolation kernels for a given set of motion vectors (e.g., BMA motion vectors). We find a generalized orthogonality condition for these kernels; optimality is achieved only if the projections of vertex motions on the local intensity gradients are statistically orthogonal to mesh-based estimation errors. Experiments show that optimal kernels are often very different from the traditional bilinear kernels, and exhibit interesting variations. The new kernels benefit a variety of applications, including motion estimated interpolation, denoising, and compression.