Robust Block-Matching Motion Estimation of Flotation Froth Using Mutual Information

Abstract

In this paper, we propose a new method for the motion estimation of flotation froth using mutual information with a bin size of two as the block matching similarity metric. We also use three-step search-and new-three-step-search as a search strategy. Mean sum of absolute difference (MAD) is widely considered in blocked based motion estimation. The minimum bin size selection of the proposed similarity metric also makes the computational cost of mutual information similar to MAD. Experimental results show that the proposed motion estimation technique improves the motion estimation accuracy in terms of peak signal-to-noise ratio of the reconstructed frame. The computational cost of the proposed method is almost the same as the standard machine vision methods used for the motion estimation of flotation froth.