@inproceedings{f9d14f83ee1e4d47b1fbe5e8433a1bb4,
title = "Reference image based color correction for multi-camera panoramic high resolution imaging",
abstract = "Maintaining color consistency across panoramic video captured by multi-camera array is a challenging problem. In an uncalibrated multi-camera array with automatic camera settings, each camera individually adjusts its parameters in accordance with the region of scene captured, independent of adjacent cameras. This leads to inconsistency in intensity and color in the stitched panoramic image. Selection of one of the images as reference for color correction may yield poor results because no individual camera image may represent the color palette of entire scene. We address these issues by capturing a separate low resolution reference color image with a field of view that encompasses entire scene. The color statistics of the reference image are used to bring each camera array image into a uniform radiance and color palette. We then estimate optimal color correction parameters using a joint pairwise optimization that minimizes overall error in stitched panorama, thus achieving a fast and robust color correction scheme for multi-camera panoramic high resolution imaging.",
keywords = "Image color analysis, Image enhancement, Image processing, Image registration, Image segmentation",
author = "Radhakrishna Dasari and Zhang, \{Dong Qing\} and Chen, \{Chang Wen\}",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 13th Conference on Computer and Robot Vision, CRV 2016 ; Conference date: 01-06-2016 Through 03-06-2016",
year = "2016",
month = dec,
day = "28",
doi = "10.1109/CRV.2016.15",
language = "English",
series = "Proceedings - 2016 13th Conference on Computer and Robot Vision, CRV 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "410--415",
editor = "Juan Guerrero",
booktitle = "Proceedings - 2016 13th Conference on Computer and Robot Vision, CRV 2016",
address = "United States",
}