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2019 | OriginalPaper | Chapter

Random Forests Based Image Colorization

Authors : Helge Mohn, Mark Gaebelein, Ronny Hänsch, Olaf Hellwich

Published in: Computer Vision, Imaging and Computer Graphics Theory and Applications

Publisher: Springer International Publishing

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Abstract

The task of image colorization, i.e. assigninging color values to grayscale images, is usually addressed by either exploiting explicit user input or very large training data sets. In contrast, the proposed method is fully automatic and uses several orders of magnitude less training images. To this aim, a Random Forest is tailored to the task of regressing plausible color value given a patch of the grayscale image. In order to improve the colorization performance, the Random Forests also includes a simple position prior. The proposed approach leads to satisfying results over various colorization tasks and compares favorably with the state of the art based on convolutional networks.

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Title: Random Forests Based Image Colorization
Authors: Helge Mohn
Mark Gaebelein
Ronny Hänsch
Olaf Hellwich
Publisher: Springer International Publishing
Book: Computer Vision, Imaging and Computer Graphics Theory and Applications
Print ISBN: 978-3-030-26755-1

Electronic ISBN: 978-3-030-26756-8

Copyright Year: 2019
DOI: https://doi.org/10.1007/978-3-030-26756-8_14

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