实现遥感相机自主辨云的小波SCM算法

A Wavelet SCM Algorithm Used to Detect Cloud in Remote Sensing Cameras

随着遥感相机分辨力的提高和幅宽的增大,星上固存和数传带宽面临巨大的挑战。提出一种多分支云判别算法,可控制相机在有云区关机停拍。首先利用计算量较小的光谱阈值判别法对云和地物粗略分类,在不能确定云或地物时,采用纹理分析方法判别。为减小误判可能,算法采用小波SCM提取纹理特征,并提出一种基于ASM和熵的双判别方式。通过对245幅遥感图像进行试验验证,证明该算法能快速准确识别云层和地物,总误判率小于5%。

The satellite;s storage device and downlink bandwidth are facing great challenges with the improvements of cameras; resolution and swath width. This paper proposed a new multi-branches cloud discrimination algorithm to control the camera stop photo in cloud area. Firstly, the spectrum threshold method is used to distinguish between clouds and ground objects roughly. Then the texture analysis method is adopted after threshold method invalid. To reduce the false alarm rate, a new method based on wavelet SCM is used to extract texture properties, and a bi-judgement method based on ASM and entropy is proposed. The algorithm has been verified by 245 remote sensing images. The experimental results show that this algorithm can detect clouds and ground objects correctly, and the false alarm rate is lower than 5%.