Microlens array grid estimation, light field decoding, and calibration
| Autor: | Schambach, Maximilian, León, Fernando Puente |
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| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | IEEE Transactions on Computational Imaging, vol. 6, pp. 591-603, 2020 |
| Druh dokumentu: | Working Paper |
| DOI: | 10.1109/tci.2020.2964257 |
| Popis: | We quantitatively investigate multiple algorithms for microlens array grid estimation for microlens array-based light field cameras. Explicitly taking into account natural and mechanical vignetting effects, we propose a new method for microlens array grid estimation that outperforms the ones previously discussed in the literature. To quantify the performance of the algorithms, we propose an evaluation pipeline utilizing application-specific ray-traced white images with known microlens positions. Using a large dataset of synthesized white images, we thoroughly compare the performance of the different estimation algorithms. As an example, we apply our results to the decoding and calibration of light fields taken with a Lytro Illum camera. We observe that decoding as well as calibration benefit from a more accurate, vignetting-aware grid estimation, especially in peripheral subapertures of the light field. Comment: \copyright 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works |
| Databáze: | arXiv |
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