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Robust Joint Image Reconstruction from Color and Monochrome Cameras

Authors :
Li, Muxingzi
Tu, Peihan
Heidrich, Wolfgang
COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)
Geometric Modeling of 3D Environments (TITANE)
Inria Sophia Antipolis - Méditerranée (CRISAM)
Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
University of Maryland [College Park]
University of Maryland System
King Abdullah University of Science and Technology (KAUST)
Susanna Donatelli, Stefan Haar
ANR-18-CE25-0007,DCore,Debogage causal pour systèmes concurrents(2018)
Source :
LNCS, BMVC 2019-30th British Machine Vision Conference, BMVC 2019-30th British Machine Vision Conference, Sep 2019, Cardiff, United Kingdom
Publication Year :
2019
Publisher :
HAL CCSD, 2019.

Abstract

International audience; Recent years have seen an explosion of the number of camera modules integratedinto individual consumer mobile devices, including configurations that contain multi-ple different types of image sensors. One popular configuration is to combine an RGBcamera for color imaging with a monochrome camera that has improved performancein low-light settings, as well as some sensitivity in the infrared. In this work we in-troduce a method to combine simultaneously captured images from such a two-camerastereo system to generate a high-quality, noise reduced color image. To do so, pixel-to-pixel alignment has to be constructed between the two captured monochrome and colorimages, which however, is prone to artifacts due to parallax. The joint image recon-struction is made robust by introducing a novel artifact-robust optimization formulation.We provide extensive experimental results based on the two-camera configuration of a commercially available cell phone.

Details

Language :
English
Database :
OpenAIRE
Journal :
LNCS, BMVC 2019-30th British Machine Vision Conference, BMVC 2019-30th British Machine Vision Conference, Sep 2019, Cardiff, United Kingdom
Accession number :
edsair.dedup.wf.001..89e89b87576f811756dca3bfaacf6a10