基于空间模糊C均值聚类和贝叶斯网络的抗噪声遥感图像变化检测

王子浩, 李轶鲲, 李小军, 杨树文

Noise-resistant change detection for remote sensing images based on spatial fuzzy C-means clustering and a Bayesian network

WANG Zihao, LI Yikun, LI Xiaojun, YANG Shuwen

表4 FLICM-SBN-CVAPS的噪声敏感度表(Kappa系数值)

Tab.4 Noise sensitivity table for FLICM-SBN-CVAPS(Kappa coefficient value)

算法 椒盐噪 声0.4% 椒盐噪 声0.6% 零均值,方差为 0.001高斯噪声 零均值,方差为0.001高 斯噪声+椒盐噪声0.2% 零均值,方差为0.001高 斯噪声+椒盐噪声0.4% 零均值,方差为0.001高 斯噪声+椒盐噪声0.6% FLICM-SBN-CVAPS 0.868 0.720 0.853 0.861 0.778 0.754 FCM-SBN-CVAPS 0.821 0.700 0.501 0.767 0.742 0.728 FCM_S1-SBN-CVAPS 0.885 0.882 0.873 0.864 0.876 0.861 FCM_S2-SBN-CVAPS 0.882 0.881 0.881 0.881 0.883 0.880 SVM-CVAPS 0.693 0.668 0.596 0.675 0.638 0.538