基于潜在半径优化策略的数字图像抠图算法

针对目标图像利用导向滤波算法进行图像抠图时参数需要根据不同图像进行人为设定的问题,提出了一种利用隐藏的支持向量机LSVM(latent support vector machine)自动设定参数的潜在半径优化的数字图像抠图算法.该方法首先是应用LSVM潜在性的思想,利用已知数据库模板训练输入目标图像的样本集,再利用样本集将导向图像和二值图像以不同半径进行分块并进行判定,确定半径值,从而能够自动产生合理参数.最后利用导向滤波器对图像进行抠图,从而优化抠图算法,最终实现抠图算法的智能化和灵活化.

A Digital Image Matting Algorithm Based on the Optimization Strategy of Latent Radius

Due to parameters is needed to be set depending on the issue of human goal-oriented to filter matting algorithms， a classifier was proposed based on component detection called LSVM (latent support vector machine). The parameters of guided radius could be automatically set so as to optimize algorithm. Firstly， for determining the radius， a potential idea of LSVM was applied which using the known database templates to train the input samples of the target image， then the sample set of the guided image and the binary image were divided into blocks with different radius which could automatically generate the reasonable parameters and optimize algorithm. At last， guided filter was used to advance matting and the intelligent and flexible of the matting algorithm was achiered.