基于改进型Potts模型的图像分割

Image Segmentation Based on Improved Potts Model

在分析Opera等人提出的能量更新算法的基础上，该文提出了改进算法。对图像预分割，将对像素的处理转换为对像素团的处理，从而加快了聚类的过程。改进了算法的采样方法，用Metropolis采样替代Gibbs采样。在成功分割静态图像的基础上，实现对视频图像序列的分割。实验结果表明该算法比原算法有更佳的分割效果，而且收敛速度比原算法快30-40倍。

Energy based Cluster Update （ECU） algorithm proposed by Ralf has its drawback that it is inefficient in sampling and slow in convergence. A new algorithm is proposed to improve the ECU algorithm. It preprocesses the image to merge single pixels to atomic region, thus processes the image on atomic region instead of pixels with the algorithm. It improves the sampling method with Metropolis sampler, which speeds up the convergence of the model. It successfully uses the algorithm on both the static images and video sequences as an application. Experimental results show that the algorithm is more efficient and has higher speed.