Abstract
This paper presents a global approach for constructing high dynamic range mosaic from multiple images with large exposure differences. By relating image intensities to scene radiances with a convenient distortion model, we robustly estimated registration parameters for the high dynamic range global mosaic (HDRGM), simultaneously estimating scene radiances and distortion parameters in a single framework. Also, a simple detail-preserving contrast reduction method is introduced.
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© 2006 Springer-Verlag Berlin Heidelberg
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Kim, DW., Hong, KS. (2006). High Dynamic Range Global Mosaic. In: Narayanan, P.J., Nayar, S.K., Shum, HY. (eds) Computer Vision – ACCV 2006. ACCV 2006. Lecture Notes in Computer Science, vol 3851. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11612032_75
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DOI: https://doi.org/10.1007/11612032_75
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-31219-2
Online ISBN: 978-3-540-32433-1
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