一种基于多分辨率与模糊聚类技术的散焦图像分割算法

带有投射光栅的散焦图像的准确分割是3维物体复原的重要环节。为了更准确地进行散焦图像分割，基于所提取的带光栅散焦图像特征，提出了一种将多分辨率分析与模糊聚类技术融合实现图像分割的算法。该算法是利用多分辨率技术来建立面向像素特征向量的多级图像联系矩阵，并在图像低分辨率级进行基于模糊聚类的区域分割。实验证明，该技术不仅克服了直接分割的困难，而且提高了分割的正确率，因此表明，该算法是有效的。

A Segmentation Algorithm for Defocused ImagesUsing Multi resolution and Fuzzy Clustering

The object segmentation of defocused images with projected illumination patterns is a primary component of 3D object recovery. A segmentation algorithm, which combines multi resolution analysis and fuzzy clustering, is proposed based on features extracted from defocused images with illumination patterns to increase the segmentation accuracy. This approach is carried out through two stages: firstly building the relational matrix of multi resolution images on their similarity measures and then implementing FCM classification at lower resolution level. The proposed technique provides a novel way of avoiding the difficulties of direct segmentation. And it increases the accuracy of object segmentation. It is shown in experiments that the proposed algorithm is of effectiveness.