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Volume: 31 | Article ID: art00015
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Learning based demosaicing and color correction for RGB-IR patterned image sensors
  DOI :  10.2352/ISSN.2470-1173.2019.15.AVM-045  Published OnlineJanuary 2019
Abstract

RGB-IR sensor combines the capabilities of RGB sensor and IR sensor in one single sensor. However, the additional IR pixel in the RGBIR sensor reduces the effective number of pixels allocated to visible region introducing aliasing artifacts due to demosaicing. Also, the presence of IR content in R, G and B channels poses new challenges in accurate color reproduction. Sharpness and color reproduction are very important image quality factors for visual aesthetic as well as computer vision algorithms. Demosaicing and color correction module are integral part of any color image processing pipeline and responsible for sharpness and color reproduction respectively. The image processing pipeline has not been fully explored for RGB-IR sensors. We propose a neural network-based approach for demosaicing and color correction for RGB-IR patterned image sensors. In our experimental results, we show that our learning-based approach performs better than the existing demosaicing and color correction methods.

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Navinprashath R R, Radhesh Bhat, "Learning based demosaicing and color correction for RGB-IR patterned image sensorsin Proc. IS&T Int’l. Symp. on Electronic Imaging: Autonomous Vehicles and Machines Conference,  2019,  pp 45-1 - 45-6,  https://doi.org/10.2352/ISSN.2470-1173.2019.15.AVM-045

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