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Super Resolution With Probabilistic Motion Estimation

delete2009-08-01
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M
Matan Protter *
M
Michael Elad
DOI:10.1109/TIP.2009.2022440delete
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Abstract

Abstract

En 中文
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).
Keywords:
Deinterlacing
probabilistic motion estimation
super resolution
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Transactions on Image Processing cover
IEEE Transactions on Image Processing
IF:
13.7
Papers:
1.0W
Citations:
8.4W

Organization

T
Technion Israel Institute of Technology
Scholars:
1.6W
Papers: 1.5W
Citations: 2.0W
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