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Non-iterative joint demosaicing and super-resolution frameworkстатья
- Авторы: Xenya Petrova, Ivan Glazistov, Sergey Zavalishin, Vladimir Kurmanov, Kirill Lebedev, Alexander Molchanov, Andrey Shcherbinin, Gleb Milyukov, Ilya Kurilin
- Сборник: Electronic Imaging
- Серия: Computational Imaging XV
- Том: 2017
- Год издания: 2017
- Издательство: Society for Imaging Science and Technology
- Местоположение издательства: United States
- Первая страница: 156
- Последняя страница: 162
- DOI: 10.2352/issn.2470-1173.2017.17.coimg-439
- Аннотация: Inverse quadratic problem of joint demosaicing and multiframe super-resolution(SR) was considered. Closed form solutions for different constant sub-pixel motions between frames were obtained and represented in the form of filter bank, which allows to compute solution of SR problem using adaptive filtering, where filters are selected depending on sub-pixel motion between frames. This procedure can be carried out using single iteration. For directional and non-directional parts of image corresponding directional or non-directional filters were applied. Color artifact reduction was achieved via usage of linear cross-channel regularizing term inspired by popular demosaicing methods. The framework includes motion estimation in Bayer domain, integrated noise reduction sub-algorithm, directionality estimation sub-algorithm, fallback logics and post-processing for additional color artifact reduction. Bank of filters is computed offline using specially developed compression techniques, which allows to reduce number of actually stored filters. Developed solution had shown superior results, compared to subsequent demosaicing and single channel SR and was tested on real raw images captured by cell phone camera in burst mode.
- Добавил в систему: Глазистов Иван Викторович