WACV '02 Proceedings of the Sixth IEEE Workshop on Applications of Computer Vision
Colorization using optimization
ACM SIGGRAPH 2004 Papers
Learning to compress images and videos
Proceedings of the 24th international conference on Machine learning
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Colorization is the process that restores colors on a gray-scale image from user-generated color assignation information. A novel approach to image compression has recently been proposed that extracts such color assignation from an input color image (We called this inverse colorization). Previous studies on inverse colorization have represented color assignation as a set of color points. However, in regions with flat color and fluctuating luminance, numerous color points are needed to correctly resore the color. Therefore, we propose a novel method of inverse colorization that represents color line segments. To extract the minimum necessary line segments from an input image, iterative updating of tentative color assignation was introduced. The experimental results revealed that our proposed method can drastically suppress color information compared to either conventional inverse colorization or JPEG.