CAJ | 학술논문

提出一种利用区域信息的航拍图像分割模型。针对GAC模型和Chan-Vese模型存在的不足，提出一种符号压力函数，该符号压力函数可以有效地增大模型的作用范围。与Chan-Vese模型相比，新模型不受初始条件的限制，进一步增大了模型的作用范围。新模型利用了图像的区域信息，可以同时将目标的内外边界分割出来。在新模型中，水平集函数不必初始化为符号距离函数，节省了计算开销。与传统的基于水平集方法的模型相比，新模型不含曲率项，实现简单。实验结果表明，与GAC模型和Chan-Vese模型相比，新模型的分割精度高于3％，分割速度快6倍以上。
제출일충이용구역신식적항박도상분할모형。침대GAC모형화Chan-Vese모형존재적불족，제출일충부호압력함수，해부호압력함수가이유효지증대모형적작용범위。여Chan-Vese모형상비，신모형불수초시조건적한제，진일보증대료모형적작용범위。신모형이용료도상적구역신식，가이동시장목표적내외변계분할출래。재신모형중，수평집함수불필초시화위부호거리함수，절성료계산개소。여전통적기우수평집방법적모형상비，신모형불함곡솔항，실현간단。실험결과표명，여GAC모형화Chan-Vese모형상비，신모형적분할정도고우3％，분할속도쾌6배이상。
Image segmentation based on level set method is one of the most widely used methods in segmenta -tion domain .Due to a large field of view for aerial image , traditional methods usually can not obtain a global segmentation, and segmentation result is often very poor .In this paper, a new segmentation method with re-gion information for aerial image is proposed .First, a new signed press function is proposed to enhance the capture range , which also can obtain global segmentation result .Second , compared with Chan-Vese model , proposed model is not limited by initial condition , and can enhance the capture range further .Third, proposed model utilizes the region information of an image , which can automatically segment inside and outside of an object simultaneously .In the proposed model , level set function doesn′t need to be initialized to signed dis-tance function, which can reduce a lot of computation cost .Moreover, the proposed model has no curvature i-tem compared with traditional level set method , and is easy for numerical implementation .Experiment results demonstrate that proposed model has a higher accuracy of 3%, and 6 times faster than GAC model and Chan-Vese model .