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Cited by 707

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Generalizing the Nonlocal-Means to Super-Resolution Reconstruction

Protter, M., Elad, M., Takeda, H., Milanfar, P.·2009·IEEE Transactions on Image Processing

Abstract

Super-resolution reconstruction proposes a fusion of several low-quality images into one higher quality result with better optical resolution. Classic super-resolution techniques strongly rely on the availability of accurate motion estimation for this fusion task. When the motion is estimated inaccurately, as often happens for nonglobal motion fields, annoying artifacts appear in the super-resolved outcome. Encouraged by recent developments on the video denoising problem, where state-of-the-art algorithms are formed with no explicit motion estimation, we seek a super-resolution algorithm of similar nature that will allow processing sequences with general motion patterns. In this paper, we base our solution on the Nonlocal-Means (NLM) algorithm. We show how this denoising method is generalized to become a relatively simple super-resolution algorithm with no explicit motion estimation. Results on several test movies show that the proposed method is very successful in providing super-resolution on general sequences.

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Metadata

Authors
Protter, M., Elad, M., Takeda, H., & Milanfar, P.
Venue
IEEE Transactions on Image Processing
Published
2009-01
Volume
18
Issue
1
Pages
36-51
ISSN
  • 1057-7149 (ISSN-L)
  • 1941-0042
OpenAlex
W2137290314
Cited by
707
References
40
FWCI
49.64
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Generalizing the Nonlocal-Means to Super-Resolution Reconstruction. https://app.cochat.ai/papers/10.1109/tip.2008.2008067
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Protter, M., Elad, M., Takeda, H., & Milanfar, P. (2009). Generalizing the Nonlocal-Means to Super-Resolution Reconstruction. IEEE Transactions on Image Processing. https://doi.org/10.1109/tip.2008.2008067

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