中文摘要：

这份报纸与稀少的乱涂为交互图象 colorization 建议一个结构知道的非局部的精力优化框架。没有明确的图象分割，我们的 colorization 技术宣传颜色到本地紧张连续的区域和遥远的质地类似的区域。我们由最近计算 k 实现非局部的原则在高度维的特征空格的邻居。特征空间包含不仅图象坐标和紧张而且与排列方向的 Gabor 小浪过滤器获得的统计质地特征。结构地图被利用放大质地特征沿着高对比的边界避免人工制品。我们在图象上显示出各种各样的试验性的结果和比较 colorization，选择 recoloring 和 decoloring，和编辑表明建议途径的有效性的进步颜色。

英文摘要：

This paper proposes a structure-aware nonlocal energy optimization framework for interactive image colo- rization with sparse scribbles. Our colorization technique propagates colors to both local intensity-continuous regions and remote texture-similar regions without explicit image segmentation. We implement the nonlocal principle by computing k nearest neighbors in the high-dimensional feature space. The feature space contains not only image coordinates and intensities but also statistical texture features obtained with the direction-aligned Gabor wavelet filter. Structure maps are utilized to scale texture features to avoid artifacts along high-contrast boundaries. We show various experimental results and comparisons on image colorization, selective recoloring and decoloring, and progressive color editing to demonstrate the effectiveness of the proposed approach.