Two-stage pyramidal convolutional neural networks for image colorization
Open Access
- 8 October 2021
- journal article
- research article
- Published by Now Publishers in APSIPA Transactions on Signal and Information Processing
- Vol. 10 (1)
- https://doi.org/10.1017/atsip.2021.13
Abstract
The development of colorization algorithms through deep learning has become the current research trend. These algorithms colorize grayscale images automatically and quickly, but the colors produced are usually subdued and have low saturation. This research addresses this issue of existing algorithms by presenting a two-stage convolutional neural network (CNN) structure with the first and second stages being a chroma map generation network and a refinement network, respectively. To begin, we convert the color space of an image from RGB to HSV to predict its low-resolution chroma components and therefore reduce the computational complexity. Following that, the first-stage output is zoomed in and its detail is enhanced with a pyramidal CNN, resulting in a colorized image. Experiments show that, while using fewer parameters, our methodology produces results with more realistic color and higher saturation than existing methods.Keywords
Funding Information
- Ministry of Science and Technology of the People's Republic of China (MOST 110-2221-E-027-040-)
This publication has 25 references indexed in Scilit:
- Real-time user-guided image colorization with learned deep priorsACM Transactions on Graphics, 2017
- Places: A 10 Million Image Database for Scene RecognitionIEEE Transactions on Pattern Analysis and Machine Intelligence, 2017
- Colorful Image ColorizationPublished by Springer Science and Business Media LLC ,2016
- Learning Representations for Automatic ColorizationPublished by Springer Science and Business Media LLC ,2016
- Let there be color!ACM Transactions on Graphics, 2016
- Deep ColorizationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2015
- Improvement to the scanning electron microscope image adaptive Canny optimization colorization by pseudo‐mappingScanning, 2014
- Fast image and video colorization using chrominance blendingIEEE Transactions on Image Processing, 2006
- Colorization using optimizationACM Transactions on Graphics, 2004
- Transferring color to greyscale imagesACM Transactions on Graphics, 2002