电光与控制, 2015, 22 (3): 45, 网络出版: 2015-03-23
多特征自适应融合的高分辨率遥感影像变化检测
Detecting the Change of High-Resolution Remote Sensing Images by Adaptive Multi-Feature Fusion
遥感影像 特征融合 变化检测 自适应调节 神经网络 remote sensing image features fusion change detection adaptive control neural network
摘要
常规的遥感影像变化检测主要基于光谱信息, 没有充分挖掘高分辨率遥感影像的多特征信息, 导致检测结果完整性不高、准确性低等问题, 针对此问题, 提出一种基于面向对象思想的多特征自适应融合的遥感影像变化检测方法。首先, 应用eCognition软件对两时相遥感影像进行分割, 提取影像对象的光谱、纹理、形状特征, 然后构建神经网络进行特征融合, 自适应地调节特征融合权值, 得到最终检测结果。实验结果表明, 多特征自适应融合的检测方法能够有效减小漏检、虚检概率, 提高检测的准确性与完整性。
Abstract
Traditional approaches for detecting the changes in remote sensing images are mainly based on spectral information of the original images without utilizing other derived features thus may result in low detection accuracy and low integrity.To solve this problem we proposed an algorithm for detecting the changes of remote sensing images based on object-oriented idea and adaptive multi-features fusion.First the eCognition was used to realize image segmentation and extract the spectral textural feature and space characteristics.A neural network was built up to realize adaptive multi-features fusion and the final detection results were obtained.The experimental results show that adaptive multi-feature fusion method can reduce the probability of missing detection and false detection and improve the accuracy and integrity of the detection result.
全卫澎, 李卫华, 李小春. 多特征自适应融合的高分辨率遥感影像变化检测[J]. 电光与控制, 2015, 22(3): 45. QUAN Wei-peng, LI Wei-hua, LI Xiao-chun. Detecting the Change of High-Resolution Remote Sensing Images by Adaptive Multi-Feature Fusion[J]. Electronics Optics & Control, 2015, 22(3): 45.