自动化学报Issue(8)：1471-1481,11.DOI:10.16383/j.aas.2015.c140734
基于图割的低景深图像自动分割
Automatic Segmentation of Images with Low Depth of Field Based on Graph Cuts
摘要
Abstract
An automatic segmentation model combined with graph cuts algorithm for low depth of field (DOF) images is proposed. Firstly, the point sharpness algorithm is improved to extract the point sharpness map of the image. In combination with color features, a four dimensional vector is constructed. Secondly, strong edges of the point sharpness map are exacted and the characteristics that the edges of clear part of an image are commonly continuous and the edges of blurred part are weak and discontinuous are used to get the preliminary foreground/background regions. Then, Gaussian mixture model (GMM) is used to model the features of point sharpness and color and by using global and local adaptiveλ the shrinking bias problem of graph cuts algorithm is improved effectively. Finally, the iterative graph cuts algorithm is used to revise the foreground/background regions. Experiments show that the proposed segmentation model is more robust and more accurate.关键词
图割/低景深/点锐度图/高斯混合模型Key words
Graph cuts/low depth of field/point sharpness map/Gaussian mixture model (GMM)引用本文复制引用
刘毅,陈圣磊,冯国富,黄兵,夏德深..基于图割的低景深图像自动分割[J].自动化学报,2015,(8):1471-1481,11.基金项目
国家自然科学基金(61473157),江苏省高校自然科学研究项目(13KJ B520013,14KJB520019)资助Supported by National Natural Science Foundation of China (61473157) and Natural Science Foundation of the Jiangsu Higher Education Institutions of China (13KJB520013,14KJB520019) （61473157）
