摘要
本文要对Simple Linear Iterative Clustering (SLIC) superpixel segmentation进行改进，
本文改进的特点：non-iterative, enforces connectivity from the start, requires lesser memory, and is faster
intro
图像分割比较难，一个较容易的解决方法就是先simplifying an image into small clusters of connected pixels called superpixels
superpixels are commonly
expected to have the following properties [7, 18]:
• Tight region boundary adherence.
• Containing a small cluster of similar pixels.
• Uniformity; roughly equally sized clusters.
• Compactness; limiting the degree of adjacency.
• Computational efficiency.
本文先提出Simple Non-Iterative Clustering (SNIC).
然后提出a polygonal segmentation algorithm called SNICPOLY, which uses SNIC superpixel segmenta- tion as the basis.
适合于geometric or man-made structures
算法
主要改变就是距离了，即公式1.
不仔细看了。