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Light-field camera calibration from raw images

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Charles-Antoine Noury
Céline Teulière
Michel Dhome

Abstract

This paper presents a new calibration method for lenslet-based plenoptic cameras. While most existing approaches require the computation of sub-aperture images or depth maps which quality depends on some calibration parameters, the proposed process uses the raw image directly. We detect micro-images containing checkerboard corners and use a pattern registration method to estimate their positions with subpixelic accuracy. We present a more complete geometrical model than previous work composed of 16 intrinsic parameters. This model relates 3D points to their corresponding image projections. We introduce a new cost function based on reprojection errors of both checkerboard corners and micro-lenses centers in the raw image space. After the initialization process, all intrinsic and extrinsic parameters are refined with a non-linear optimization. The proposed method is validated in simulation as well as on real images.
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Dates and versions

hal-01657735 , version 1 (29-10-2020)

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Charles-Antoine Noury, Céline Teulière, Michel Dhome. Light-field camera calibration from raw images. International Conference on Digital Image Computing: Techniques and Applications (DICTA’17), Nov 2017, Sydney, Australia. pp.1-8, ⟨10.1109/DICTA.2017.8227459⟩. ⟨hal-01657735⟩
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