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Microlens Array Grid Estimation, Light Field Decoding, and Calibration

Schambach, Maximilian; Puente León, Fernando

Abstract:
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 raytraced 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.

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Originalveröffentlichung
DOI: 10.1109/tci.2020.2964257
Zugehörige Institution(en) am KIT Institut für Industrielle Informationstechnik (IIIT)
Publikationstyp Zeitschriftenaufsatz
Publikationsdatum 06.01.2020
Sprache Englisch
Identifikator ISSN: 2333-9403, 2573-0436
KITopen-ID: 1000121019
Erschienen in IEEE transactions on computational imaging
Band 6
Seiten 591–603
Schlagwörter Light field camera, calibration, light field decoding
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