Misaligned Image Integration With Local Linear Model
Author(s) -
Tatsuya Baba,
Ryo Matsuoka,
Keiichiro Shirai,
Masahiro Okuda
Publication year - 2016
Publication title -
ieee transactions on image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.778
H-Index - 288
eISSN - 1941-0042
pISSN - 1057-7149
DOI - 10.1109/tip.2016.2535329
Subject(s) - signal processing and analysis , communication, networking and broadcast technologies , computing and processing
We present a new image integration technique for a flash and long-exposure image pair to capture a dark scene without incurring blurring or noisy artifacts. Most existing methods require well-aligned images for the integration, which is often a burdensome restriction in practical use. We address this issue by locally transferring the colors of the flash images using a small fraction of the corresponding pixels in the long-exposure images. We formulate the image integration as a convex optimization problem with the local linear model. The proposed method makes it possible to integrate the color of the long-exposure image with the detail of the flash image without causing any harmful effects to its contrast, where we do not need perfect alignment between the images by virtue of our new integration principle. We show that our method successfully outperforms the state of the art in the image integration and reference-based color transfer for challenging misaligned data sets.
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