Application of fractal analysis in image motion estimation
Zhiyong Shi, Fengchun Tian, Yande Wang, Jian Ran · The Imaging Science Journal · 2017
The motion estimation, as a key technique, affects the effect of image processing. However, many matching criteria based on the similarity of image grey value probably lead to the inaccurate motion estimation. In order to improve the performance of motion estimation, a novel image matching criterion is proposed on the basis of the fractal theory. The proposed criterion not only considers the grey-level similarity of the same object, but also takes into account the invariance of the fractal dimension of the same object. Therefore, the optimal and accurate matching between anchor object and reference objects can be better ensured. The experimental results show that the estimated motion vector of the proposed method is more approximate to the true motion vector than that of the traditional methods. What is more, the peak signal-to-noise ratio value of the image is improved by the proposed criterion. Meantime, the computational complexity is increased slightly.