Automatic Image Colorization based on Feature Lines
Automatic Image Colorization based on Feature Lines
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DOI：
10.5220/0005676401260133
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Van Nguyen;Vicky Sintunata;T. Aoki
中科院分区：
文献类型：
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作者：
Van Nguyen;Vicky Sintunata;T. Aoki
图像自动彩色化是图像处理领域的研究热点之一。这一领域最关键的任务是如何设计一种算法来定义从参考图像(S)传播到目标图像的合适颜色。换句话说，我们需要确定参考图像和目标图像中的两个像素是否具有相似的颜色。在以往的方法中，介绍了许多方法，主要是基于局部特征匹配算法。然而，它们仍然存在一些缺陷，而且耗时较长。本文提出了一种新的基于特征线的图像自动彩色化方法。要素线是我们的新概念，它加强了颜色线的概念。它表示每个像素特征向量在直线周围拉长的分布，以便我们能够将相似的特征像素组装成一条特征线。通过引入这种新技术，基准图像和目标图像之间的像素匹配得到了精确的执行。实验结果表明，与以往的颜色分配方法相比，该方法获得了更平滑、更均匀、更自然的颜色分配。
Automatic image colorization is one of the attractive research topics in image processing. The most crucial task in this field is how to design an algorithm to define appropriate color from the reference image(s) for propagating to the target image. In other words, we need to determine whether two pixels in reference and target images have similar color. In previous methods, many approaches have been introduced mostly based on local feature matching algorithms. However, they still have some defects as well as time-consuming. In this paper, we will present a novel automatic image colorization method based on Feature Lines. Feature Lines is our new concept, which enhances the concept of Color Lines. It represents the distribution of each pixel feature vector as being elongated around the lines so that we are able to assemble the similar feature pixels into one feature line. By introducing this new technique, pixel matching between reference and target images performs precisely. The experimental achievements show our proposed method achieves smoother, evener and more natural color assignment than the previous methods.