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云噪声是光学卫星影像的常见问题,为了衡量云噪声对影像融合带来的影响,本文以高通滤波融合算法为例进行分析,指出云与地物的均值相差越大,云对影像融合的影响越大,并提出了一种针对含云影像的融合方法,即联合云检测与高通滤波的含云影像融合方法。该方法首先利用NIR/R-OTSU云检测算法实时进行云检测,判别出影像中的云覆盖区域;其次采用局部优化策略利用高通滤波融合方法分块对非云区域进行处理,得到融合影像。利用资源三号多光谱和正视全色影像进行融合实验,结果表明,本文算法比高通滤波融合方法、亮度色度饱和度(intensity hue saturation,IHS)变换融合方法、Pansharp融合方法更适用于含云影像的融合处理。
Cloud noise is a common problem in optical satellite imagery. In order to measure the influence of cloud noise on image fusion, this paper uses high-pass filter fusion algorithm as an example to analyze, pointing out that the greater the difference between cloud and feature mean, the cloud effect on image fusion The larger the fusion method, the fusion method of cloud detection and high-pass filtering is proposed. Firstly, cloud detection is performed by using NIR / R-OTSU cloud detection algorithm to identify the cloud coverage area in the image. Secondly, a local optimization strategy is used to process the non-cloud regions by using the high-pass filtering fusion method to obtain a fusion image. The results show that the proposed algorithm is better than the high-pass filter fusion method, the intensity hue saturation (IHS) transform fusion method and the Pansharp fusion method, Image fusion processing.