A Colorization Method Based on Fuzzy Clustering and Distance Transformation
Zhaohui Zhang, HuiQing Cui, Hanqing Lu, RuiQing Chen, Yukun Yan · 2009
This paper proposes a novel colorization algorithm for monochrome still images based on fuzzy clustering and distance transformation. Given small amount of typical color scribbles manually marked on the input grayscale image, the followed colorization process consists of four main steps: color scribble extraction, distance transformation and spatial weight estimation, fuzzy clustering and luminance weight estimation, and weighted color blending. By propagating the local color hints from the given scribbles to the whole grayscale image, the final output color image can be produced. Experimental results show that when the content of grayscale image is relatively simple, the proposed colorization method can efficiently gain a good colorized image with only a small number of scribbles. The algorithm is simple and easy to implement. Moreover, it takes only several seconds to complete the colorization process but can get visually vivid result.