论文标题
Power-Slic：快速超级像素分割
Power-SLIC: Fast Superpixel Segmentations by Diagrams
论文作者
论文摘要
超级像素算法将像素分组具有相似的颜色和其他低级特性，越来越多地用于预处理图像分割。近年来，已经将重点放在开发几何超级像素方法上，以促进促进几何图像特征的提取和分析。基于图的超级像素方法在几何方法中产生紧凑且稀疏表示的超像素很重要。将广义平衡功率图引入超像素的字段，我们提出了一种称为Power-Slic的图方法。 Power-Slic是生成分段二次边界的第一个几何超级像素方法。它的速度，具有快速最先进的方法的竞争力，是图表方法前所未有的。广泛的计算实验表明，在边界召回中，Power-Slic优于现有图的方法，在分割误差，可实现的分割精度和压缩质量下。此外，Power-Slic对高斯噪音具有强大的功能。
Superpixel algorithms grouping pixels with similar color and other low-level properties are increasingly used for pre-processing in image segmentation. In recent years, a focus has been placed on developing geometric superpixel methods that facilitate the extraction and analysis of geometric image features. Diagram-based superpixel methods are important among the geometric methods as they generate compact and sparsely representable superpixels. Introducing generalized balanced power diagrams to the field of superpixels, we propose a diagram method called Power-SLIC. Power-SLIC is the first geometric superpixel method to generate piecewise quadratic boundaries. Its speed, competitive with fast state-of-the-art methods, is unprecedented for diagram approaches. Extensive computational experiments show that Power-SLIC outperforms existing diagram approaches in boundary recall, under segmentation error, achievable segmentation accuracy, and compression quality. Moreover, Power-SLIC is robust to Gaussian noise.
