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Erschienen in:
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2014 | OriginalPaper | Buchkapitel

3. Super Resolution

verfasst von : Hyo-Moon Cho

Erschienen in: Algorithm & SoC Design for Automotive Vision Systems

Verlag: Springer Netherlands

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Abstract

We introduced, in this chapter, what the definition of a super resolution is and what the key approaching methods for major super resolution algorithms are. Numerous super resolution algorithms have based on the observation model and they have followed the warp-blur sequence. But, some cases which have large movements and warp factors such as video by taking in a vehicle are worse than normal interpolation methods. We introduce the smart and robust registration algorithm with rotation and shift estimation. To reduce the registration error, this algorithm decides the optimal reference image even other super resolution algorithms discard this registration error. This algorithm follows the warp-blur observation model because the blurring parameter is much bigger than warp parameter for camera rotation and/or vibration.

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Vorheriges Kapitel Lens Correction and Gamma Correction
Nächstes Kapitel Image Enhancement for Improving Object Recognition
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Metadaten
Titel
Super Resolution
verfasst von
Hyo-Moon Cho
Copyright-Jahr
2014
Verlag
Springer Netherlands
Buch
Algorithm & SoC Design for Automotive Vision Systems

Print ISBN: 978-94-017-9074-1

Electronic ISBN: 978-94-017-9075-8

Copyright-Jahr: 2014

DOI
https://doi.org/10.1007/978-94-017-9075-8_3

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