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Algorithm & SoC Design for Automotive Vision Systems pp 41–72Cite as

Super Resolution

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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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  1. Engineering Faculty, Universiti Malaya, Kualar Lumpur, Malaysia

    Hyo-Moon Cho

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  1. Yonsei University, Seoul, Korea, Republic of (South Korea)

    Jaeseok Kim

  2. Hanyang University, Ansan, Korea, Republic of (South Korea)

    Hyunchul Shin

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Cho, HM. (2014). Super Resolution. In: Kim, J., Shin, H. (eds) Algorithm & SoC Design for Automotive Vision Systems. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9075-8_3

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