目的 超像素(superpixel)是近年来快速发展的一种图像预处理技术,它将图像快速分割为一定数量的具有语义意义的子区域,相比于传统处理方法中的基本单元——像素,超像素更有利于局部特征的提取与结构信息的表达,并且能够大幅度降低后续处理的计算复杂度,在计算机视觉领域尤其是图像分割中得到了广泛的应用,为使国内外研究者对超像素理论及其在图像分割中的应用有一个比较全面的认识,对其进行系统综述.方法 以图像分割为应用背景,在广泛调研文献特别是超像素最新发展成果的基础上,结合对比实验,对每种方法的基本思想、方法特点进行总结,并对超像素分割目前存在的局限性进行说明,对未来可能发展方向进行展望.结果 不同的超像素分割算法在分割思想、性能特点上各不相同.当前的超像素方法普遍在超像素数量、紧密度与分割质量、算法实用性之间存在相互制约,同时对于某些特殊目标的分割也难以取得较好的结果.结论 超像素作为一种有效的图像预处理手段具有较高的研究价值,但针对目前超像素存在的一些局限性还需要进行深入的研究.

Objective Superpixel methods are image pre-processing technologies that have rapidly developed in recent years. These methods can segment an image into a certain amount of semantically meaningful sub-regions. Compared with the basic element pixels in the traditional image processing methods, superpixels have better abstraction of image local features and better representations of structural information. Furthermore, superpixels can dramatically reduce the complexity of the subsequent processing. Given these significant advantages, superpixels have been widely used in computer vision, particularly in image segmentation. Considering its theoretical value, this study comprehensively reviews the existing superpixel methods and their applications in image segmentation.Method The history of superpixel segmentation is reviewed, and the superpixel segmentation algorithms are compared in experiments using evaluation metrics to present their performance in superpixel segmentation. Then, the applications of superpixels in image segmentation are categorized and introduced. Finally, the existing limits of the superpixel segmentation algorithms are shown, and the implicit directions for future research on superpixels are concluded.Result The fundamental concepts, advantages, and disadvantages of the superpixel segmentation algorithms and the applications of superpixels in image segmentation are reviewed. The limits of superpixel segmentation algorithms are presented on the basis of several experiments.Conclusion As effective pre-processing technologies, superpixel methods have relatively high research value. However, the limitations of superpixels require further research. These limitations include contradictions between the amount of superpixels and the segmentation quality, the superpixel segmentations of some particular objects, and so on.