1. 河海大学计算机与信息学院,江苏,南京,210098
2. 河海大学通信与信息系统工程研究所,江苏,南京,210098
3. 河海大学计算机与信息学院江苏南京,210098
4. 河海大学通信与信息系统工程研究所江苏南京,210098
纸质出版:2011
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徐立中, 李敏, 石爱业, 等. 受昆虫视觉启发的多光谱遥感影像特征检测器模型[J]. 电子学报, 2011,39(11):2497-2501.
XU Li-zhong, LI Min, SHI Ai-ye, et al. Feature Detector Model for Multi-Spectral Remote Sensing Image Inspired by Insect Visual System[J]. Acta Electronica Sinica, 2011, 39(11): 2497-2501.
本文受昆虫视觉系统时空域特征交互作用机理的启发
跳出传统遥感影像特征提取算法的研究思路
在无需考虑局部窗口尺寸和参数估计的条件下
提出利用波段交叉相关提取边缘纹理特征信息的多光谱遥感影像特征检测器模型.通过频谱域分析证明该模型可以综合光谱信息和空间信息对边缘纹理特征产生响应
具有较好的普适性和较强的抗噪能力.本文还将该特征检测器模型带入遥感影像重构算法中
获得了高频信息丰富的重构效果
验证了特征检测器模型的有效性.
Inspired by the theory of interaction between spatial feature and temporal feature in insect visual system
beyond the traditional feature extraction method
this paper proposes a feature detector model for multi-spectral remote sensing image
which is based on the cross correlation of multi-band
and without the limitation of the global window size and parameters.By the analysis in frequency domain
it showed that this feature detector model can respond to the edge and texture by integrating spectral information and spatial information.Beside this
the proposed feature detector model was effective and robust to the random noise.This paper also brings the feature detector model into reconstruction algorithm of remote sensing image.Reconstructed results validate the effectiveness of the feature detector model
which contains rich high-frequency information.
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