A Practical Monochrome Video Colorization Framework for Broadcast Program Production

نویسندگان

چکیده

Techniques of using convolutional neural networks (CNNs) to colorize monochrome still images have been widely researched. However, the results automatic colorization are often different from user's intentions and historical fact. A lot color correction work needs be done in order produce a colorized video. This is major problem situations such as broadcasting production where footage must appropriately accordance with In this article, we propose practical video framework that can easily reflect intentions. The proposed uses combination two CNNs-a user-guided still-image-colorization CNN color-propagation CNN-that allows performed efficiently. produces key frames by colorizing several target on basis user-specified colors color-boundary information. automatically colorizes entire frames, while suppressing discontinuous changes between frames. quantitative evaluation showed it possible reflecting intention less effort than earlier methods.

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ژورنال

عنوان ژورنال: IEEE Transactions on Broadcasting

سال: 2021

ISSN: ['0018-9316', '1557-9611']

DOI: https://doi.org/10.1109/tbc.2020.3028343