计算机科学 ›› 2022, Vol. 49 ›› Issue (11A): 211200100-6.doi: 10.11896/jsjkx.211200100
祁颖, 柴艳妹
QI Ying, CHAI Yan-mei
摘要： 海冰分割是遥感图像处理领域的重要研究方向之一。由于高分辨率遥感海冰图像较大,采用SLIC构建超像素块,可为后续的再分割节省时间。SLIC虽能产生形状规则均匀的超像素块,但该算法的初始种子点对噪声敏感、分割精度与运行速度欠佳。因此,提出了一种基于改进的SLIC与聚类算法相结合的高分辨率遥感海冰图像分割算法。针对噪声敏感问题,首先采用各向异性扩散滤波进行图像的预处理,在保证图像完整性的同时有效降噪;其次,用L-p范数对传统SLIC算法中的欧氏距离度量进行扩展,以获取更优分割效果;最后,在SLIC超像素块的基础上分别采用DBSCAN和K-Means聚类算法进行精确分割,通过性能对比得到最优结果。实验结果表明,改进后的SLIC结合K-Means的分割方法的性能优于MRF算法及SLIC与DBSCAN相结合的算法,取得了较为理想的分割结果。
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