Paper
7 March 2014 Video colorization based on optical flow and edge-oriented color propagation
Mayu Otani, Hirohisa Hioki
Author Affiliations +
Proceedings Volume 9020, Computational Imaging XII; 902002 (2014) https://doi.org/10.1117/12.2037496
Event: IS&T/SPIE Electronic Imaging, 2014, San Francisco, California, United States
Abstract
We propose a novel video colorization method based on sparse optical flow and edge-oriented color propagation. Colorization is a process of adding color to monochrome images or videos. In our video colorization method, it is assumed that key frames are appropriately selected out of a grayscale video stream and are properly colorized in advance. Once key frames are colorized, our method colorizes all the remaining grayscale frames automatically. It is also possible to colorize key frames semi-automatically by our method. For colorizing a grayscale frame between a pair of colorized key frames, sparse optical flow is computed first. The optical flow consists of reliable motion vectors around strong feature points. The colors around feature points of key frames are then copied to the grayscale frame according to the estimated motion vectors. Those colors are then propagated to the rest of the grayscale frame. Colors are blended appropriately during the propagation process. A pair of accuracy and priority measures is introduced to control how the color propagation proceeds. To successfully propagate colors, it is important not to wrongly spread colors across edges. For this purpose, a set of neighboring pixels is adaptively selected not to include edge-like areas and thus not to spread colors across edges. To evaluate effectiveness of our method, image colorization and video colorization were performed. Experimental results show that our method can colorize images and videos better than previous methods when there are edges. We also show that the proposed method enables us to easily modify colors in colored video streams.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mayu Otani and Hirohisa Hioki "Video colorization based on optical flow and edge-oriented color propagation", Proc. SPIE 9020, Computational Imaging XII, 902002 (7 March 2014); https://doi.org/10.1117/12.2037496
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Video

Optical flow

Video processing

Motion estimation

Image processing

Neptunium

Reliability

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