工程科学学报2016，Vol.38Issue(6)：876-885,10.DOI:10.13374/j.issn2095-9389.2016.06.019
流形正则化多核模型的模糊红外目标提取
Extraction of blurred infrared targets based on a manifold regularized multiple-kernel model
摘要
Abstract
Specific to the problem of infrared target extraction with blurred edges, this article introduces an extraction method based on a manifold regularized multiple kernel semi-supervised classification model. Firstly, the maximum variance of inter-class ( OTSU) method is used to compute the initial segmentation threshold, and the certain target and background areas and the uncertain blurred edge area are determined. Then, local space sets of pixels are constructed in each area, the multiple-kernel functions are used to map the grayscale mean and variance in local space, and the location information feature in local space is obtained by manifold regu-larization ( MR) . On the basis of features, a semi-supervised classification model is established to classify the local space sets of pixels in the blurred edge area. Finally, the optimal segmentation threshold is computed. Experiments with comparisons show that this meth-od is efficient and less in time-consuming.关键词
模糊边缘/目标提取/核函数/流形正则化Key words
blurred edge/target extraction/kernel functions/manifold regularization分类
信息技术与安全科学引用本文复制引用
杨焘,付冬梅..流形正则化多核模型的模糊红外目标提取[J].工程科学学报,2016,38(6):876-885,10.基金项目
国家自然科学基金资助项目(61272358) （61272358）
