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Super Resolution With Probabilistic Motion Estimation

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2 Author(s)
Matan Protter ; Comput. Sci. Dept., Technion - Israel Inst. of Technol., Haifa, Israel ; Michael Elad

Super-resolution reconstruction (SRR) has long been relying on very accurate motion estimation between the frames for a successful process. However, recent works propose SRR that bypasses the need for an explicit motion estimation [11], [15]. In this correspondence, we present a new framework that ultimately leads to the same algorithm as in our prior work [11]. The contribution of this paper is two-fold. First, the suggested approach is much simpler and more intuitive, relying on the classic SRR formulation, and using a probabilistic and crude motion estimation. Second, the new approach offers various extensions not covered in our previous work, such as more general re-sampling tasks (e.g., de-interlacing).

Published in:

IEEE Transactions on Image Processing  (Volume:18 ,  Issue: 8 )