A New M-Estimator Approach for Global Motion Estimation.
ABSTRACT Global motion estimation (GME) is an extensively used tool in a variety of video processing applications. The major challenge in this field is the presence of large foreground objects. There is a wide variety of algorithms addressing this problem. The major shortcoming of these algorithms is inconsistent performance over several video sequences. In this paper, we propose a GME approach that is fully automatic, can successfully handle large foreground objects and provides consistent results over a range of different video sequences. The proposed method initially coarsely determines the foreground pixels by a clustering technique. The effect of remaining foreground pixels in the estimation process are then reduced by using a modified Lorentzian estimator. Experimental results prove the superiority and consistency of the proposed method compared to some recent approaches.
Conference Proceeding: Improved global motion estimation using prediction and early termination[show abstract] [hide abstract]
ABSTRACT: Global motion compensation is an important tool to achieve high coding efficiency in many advance video coding systems such as MPEG-4. However, its computational complexity is very high. Fast algorithms are needed. In this paper, we propose an improvement to the global motion estimation algorithm used in the MPEG-4 VM coder. We achieve this by introducing two new techniques: motion vector prediction and early termination, which we applied successfully in local motion estimation. Simulation results suggest that the proposed method can reduce computation considerably without perceptual degradation.Image Processing. 2002. Proceedings. 2002 International Conference on; 02/2002
- [show abstract] [hide abstract]
ABSTRACT: This contribution presents a powerful method for real-time capable global motion estima-tion. Up to now no further solutions are known to the authors. Global motion estima-tion is a great tool in MPEG-4 coding pro-cess to improve overall visual quality. The main disadvantage of the reference imple-mentation in the current Verification Model is an unacceptable low computation speed. By means of consequently speed optimized algo-rithms a 600 MHz Intel Pentium has shown to be sufficient for the aquired task.
- [show abstract] [hide abstract]
ABSTRACT: This paper proposes a novel image super-resolution (SR) algorithm in a robust estimation framework. SR estimation is formulated as an optimization (minimization) problem whose objective function is based on robust M-estimators and its solution yields the SR output. The novelty of the proposed scheme lies in the selection of this class of estimators and the incorporation of information-theoretic similarity measures. Such a choice helps in dealing with violations (outliers) of the assumed mathematical model that generated the low-resolution images from the "unknown" high-resolution one. The proposed approach results in high-resolution images with no estimation artifacts. Experimental results demonstrate its superior performance in comparison to both L<sub>1</sub> and L<sub>2</sub> estimation in terms of robustness and speed of convergence.Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2007, April 15-20, 2007, Honolulu, Hawaii, USA; 01/2007 · 4.63 Impact Factor