A Nonlinear L 1 -Norm Approach for Joint Image Registration and Super-Resolution
This letter proposes a nonlinear L sub(1)-norm approach for joint image registration and super-resolution (SR). Image SR is the fusion of multiple low-resolution (LR) images to produce a high-resolution (HR) image. Conventional SR algorithms are sensitive to the initial registration error and outlie...
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Veröffentlicht in: | IEEE signal processing letters 2009-11, Vol.16 (11) |
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Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
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Online-Zugang: | Volltext |
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Zusammenfassung: | This letter proposes a nonlinear L sub(1)-norm approach for joint image registration and super-resolution (SR). Image SR is the fusion of multiple low-resolution (LR) images to produce a high-resolution (HR) image. Conventional SR algorithms are sensitive to the initial registration error and outliers in the LR images. In view of this, we present a new SR method to address these problems using L sub(1)-norm optimization in joint image registration and HR image reconstruction. Experimental results show that the proposed method is effective in handling these issues in the HR image reconstruction. |
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ISSN: | 1070-9908 |
DOI: | 10.1109/LSP.2009.2028106 |