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In this paper, we present a frame rate upconversion method using optical flow motion estimation and a patch-based reconstruction scheme. First, forward and backward motion vectors (MVs) are obtained using an optical flow algorithm, and reconstructed versions of the current and previous frames are generated by our patch-based reconstruction scheme. Using the original and reconstructed versions of the current and previous frames, two mismatch masks are obtained. Then, two versions of the middle frame are generated using a patch-based scheme, with estimated MVs and the current and previous frames. Finally, a middle mask, which identifies the mismatch areas of the two middle frames, is reconstructed. Using these three masks, the best candidates for interpolation are selected and fused to obtain the final middle frame. Due to the patch-based nature of our reconstruction scheme, most of the holes and cracks will be filled. Although there is always a probability of having holes, the size and number of such holes are much smaller than those that would be generated using pixel-based mapping. The rare holes are filled using existing hole-filling algorithms. The experimental results and a comparison of our method with existing algorithms show that our method performs better in terms of both objective and subjective quality of the final interpolated frames. The average peak signal-to-noise ratio (PSNR) improvement of our method is 1–2 dB. [ABSTRACT FROM AUTHOR]

Abstract: This work presents a new method for motion estimation of tagged cardiac magnetic resonance sequences based on variational techniques. The variational method has been improved by adding a new term in the optical flow equation that incorporates tracking points with high stability of phase. Results were obtained through simulated and real data, and were validated by manual tracking and with respect to a reference state-of-the-art method: harmonic phase imaging (HARP). The error, measured in pixels per frame, obtained with the proposed variational method is one order of magnitude smaller than the one achieved by the reference method, and it requires a lower computational cost. [Copyright &y& Elsevier]