Fusion of Cloudy Opical Satellite Imagery by Cloud Detection and HPF Pass Filtering

Noise from clouds is a common problem in optical satellite image processing. The high pass filter (HPF) fusion method is analyzed as a way to estimate the influence of cloud noise during image fusion. An approach combining cloud detection with HPF is introduced that refines the results of image fusion containing clouds. A, NIR/R-OTSU cloud detection approach is employed for real-time cloud detection, thus areas covered by clouds can be identified. A local optimization strategy is adopted in image fusion with HPF in cloudless blocks to get the fused image. Merged multispectral and panchromatic iZY-3 satellite image results show that the algorithm discussed in this paper performs better than HPF, IHS transform and Pansharp methods for merging images with clouds.