摘要
针对复杂地物背景下的城区红外遥感图像的云层干扰问题,提出了一种基于图像特征提取、区域投票表决和阈值分割的云层检测方法。对图像进行去噪和归一化拉伸处理,再进行多特征提取,并通过提取的特征向量对图像进行分区域云层投票表决,最后根据表决结果和分形特征度量矩阵进行阈值计算和阈值分割,并通过形态学处理得到精确的云层区域。统计检测结果显示算法对不同时刻的数据检测准确率在91%以上,证明了算法的适用性和有效性,为红外遥感图像的信息处理提供了有效的技术支持。
Aiming at the problem of infrared remote sensing cloud detection under complex surface features background, a novel cloud detection algorithm based on image feature extraction, regional voting and threshold segmentation is proposed. Denoising and normalized stretching are performed on image. The multi-features are extracted and cloud discrimination is executed in sub-region using the extracted feature vectors. The precise cloud regions are obtained through threshold segmentation based on discrimination results and fractal characteristics. Test results show that the accuracy of image recognition is above 91%. The applicability and effectiveness of the algorithm is verified by large quantities of measured data and it provides effective technical support for the information processing of infrared remote sensing image.
出处
《中国激光》
EI
CAS
CSCD
北大核心
2012年第11期121-126,共6页
Chinese Journal of Lasers
基金
"十二五"部委预研项目(9140C800201070C80)资助课题
关键词
图像处理
红外遥感
云层检测
特征提取
阈值分割
复杂背景
image processing
infrared remote sensing
cloud detection
feature extraction
threshold segmentation
complex background
作者简介
李志军（1983-），男，博士研究生，主要从事红外图像处理方面的研究。E-mail：lzj19821202@sina．com
导师：陈曾平（1967-），男，博士，教授，主要从事精确制导自动目标识别方面的研究。E-mail：atrchen@163．com
