Most digital cameras today employ Bayer Color Filter Arrays in front of the camera sensor. In order to create a true-color image, a demosaicing step is required introducing image blur and artifacts. Special sensors like the Foveon X3 circumvent the demosaicing challenge by using pixels lying on top of each other. However, they are not commonly used due to high production cost and low flexibility. In this work, a multi-color multi-view approach is presented in order to create true-color images. Therefore, the red-filtered left view and the blue-filtered right view are registered and projected onto the green-filtered center view. Due to the camera offset and slightly different viewing angles of the scene, object occlusions might occur for the side channels, hence requiring the reconstruction of missing information. For that, a novel local linear regression method is proposed, based on disparity and color similarity. Simulation results show that the proposed method outperforms existing reconstruction techniques by on average 5 dB.
Daniel Kiesel, Thomas Richter, Jürgen Seiler, André Kaup;, "Color Channel Reconstruction for Multi-Color Multi-View Images Using Disparity and Color Similarity-based Local Linear Regression" in Proc. IS&T Int’l. Symp. on Electronic Imaging: Image Sensors and Imaging Systems, 2018, pp 292-1 - 292-6, https://doi.org/10.2352/ISSN.2470-1173.2018.11.IMSE-292