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A Colorization Method based on Fuzzy Clustering and Distance Transformation

机译:一种基于模糊聚类和距离变换的彩色方法

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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.
机译:本文提出了一种基于模糊聚类和距离变换的单色静态图像的一种新型色彩算法。考虑到少量典型的颜色涂鸦在输入灰度图像上手动标记,所谓的着色过程由四个主步骤组成:颜色涂鸦提取,距离变换和空间重量估计,模糊聚类和亮度重量估计和加权颜色混合。通过将局部颜色提示传播到整个灰度图像到整个灰度图像,可以产生最终输出彩色图像。实验结果表明,当灰度图像的含量相对简单时,所提出的彩色方法可以有效地利用少量涂鸦获得良好的彩色图像。算法简单易于实现。此外,完成着色过程只需要几秒钟,但可以得到视觉上生动的结果。

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