H. Mahdavi-Nasab, Shohreh Kasaei,
Volume 1, Issue 2 (4-2005)
Abstract
Motion estimation and compensation is an essential part of existing video coding
systems. The mesh-based motion estimation (MME) produces smoother motion field, better
subjective quality (free from blocking artifacts), and higher peak signal-to-noise ratio
(PSNR) in many cases, especially at low bitrate video communications, compared to the
conventional block matching algorithm (BMA). However, the iterative refinement process
of MME is computationally much costly and makes the method impractical in real- (or near
real-) time systems. Also, eliminating the iterative refinement step deteriorates the motion
estimation result. In this paper, we propose motion adaptive interpolation schemes for noniterative
MME, which use BMA to compute the motion vectors (MVs) of mesh nodes. The
proposed algorithm aims at compromising the MME and BMA by modifying the
interpolation patterns (IPPs) of the MME in an adaptive manner, based on the MVs of
mesh nodes. Experimental results show notable rate-distortion improvement over both
BMA and conventional non-iterative MME, with acceptable visual quality and system
complexity, especially when applied to sequences with medium to high motion activities.
S.m.reza Soroushmehr, Shadrokh Samavi, Shahram Shirani,
Volume 1, Issue 2 (4-2005)
Abstract
In this paper a new method for determining the search area for motion estimation
algorithm based on block matching is suggested. In the proposed method the search area is
adaptively found for each block of a frame. This search area is similar to that of the full
search (FS) algorithm but smaller for most blocks of a frame. Therefore, the proposed
algorithm is analogous to FS in terms of regularity but has much less computational
complexity. To find the search area, the temporal and spatial correlations among the
motion vectors of blocks are used. Based on this, the matched block is chosen from a
rectangular area that the prediction vectors set out. Simulation results indicate that the
speed of the proposed algorithm is at least 7 times better than the FS algorithm.
