摘要
研究遥感图像特征准确提取问题。遥感图像采集过程中,经常受到天空不定项云层干扰,云层会大幅反射遥感射线,导致遥感成像中存在碎云杂波,造成遥感图像中关键特征模糊、丢失等问题。传统的图像分割算法根据单一阀值设定滤波值,很难对这种随机性的碎云杂波干扰建立有效的过滤模型,造成特征分割结果偏差较大。为解决上述问题,提出了一种抗碎云杂波干扰的遥感图像特征提取算法。建立灰度增强模型,对遥感图像进行增强处理,提高图像的对比度,为特征提取提供准确的数据基础。利用最小二乘法,实现碎云杂波干扰环境下的遥感图像特征提取。实验结果表明,这种算法能够有效提高遥感图像特征提取的准确性。
This paper proposed a remote sensing image feature extraction algorithm based on crushing cloud clutter interference. Firstly, we established a gray enhancement model for remote sensing image enhancement processing and improved the image contrast to offer accurate data base for feature extraction. By using least squares method, we realized broken cloud clutter interference environment of remote sensing image feature extraction. The experimental results show that this algorithm can effectively improve the accuracy of remote sensing image feature extraction.
出处
《计算机仿真》
CSCD
北大核心
2013年第6期222-225,400,共5页
Computer Simulation
关键词
杂波干扰
遥感图像
特征提取
Clutter interference
Remote sensing image
Feature extraction
