{"title":"光学遥感卫星图像的多时相云像元重建方法","authors":"Huiqian Liu, Ruofei Zhong, Haiyin Wang, Shiyong Wu, Qingyang Li, Cankun Yang","doi":"10.2174/2210298102666220616114622","DOIUrl":null,"url":null,"abstract":"\n\nThe existence of cloud pixels reduces the practicability of optical satellite remote sensing data.\n\n\n\nExisting cloud reconstruction methods generally cannot solve the following problems:(1)Large-scale thick cloud cannot be well reconstructed. (2)There are high requirements for reconstructed data. (3)Most data used to reconstructed are single temporal images.\n\n\n\nIn order to overcome these problems, a new multi temporal weighted aggregation method is proposed. Specifically, we adopt a multi-temporal iterative aggregation method for cloud pixels to reconstruct and a multi-temporal weighted aggregation method for cloud shadow pixels to reconstruct.\n\n\n\nFinally, the experiment proves that our method can quickly and accurately complete the cloud reconstruction, and under the effective uniform color strategy, a cloud- free image with accurate geometric position and uniform gray scale can be obtained.\n\n\n\nExperiments prove that the pixel reconstruction method proposed in this paper has achieved good cloud and cloud shadow pixel reconstruction effects in different types of ground objects.\n","PeriodicalId":184819,"journal":{"name":"Current Chinese Science","volume":"164 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-temporal cloud pixels reconstruction method for optical remote sensing satellite images\",\"authors\":\"Huiqian Liu, Ruofei Zhong, Haiyin Wang, Shiyong Wu, Qingyang Li, Cankun Yang\",\"doi\":\"10.2174/2210298102666220616114622\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n\\nThe existence of cloud pixels reduces the practicability of optical satellite remote sensing data.\\n\\n\\n\\nExisting cloud reconstruction methods generally cannot solve the following problems:(1)Large-scale thick cloud cannot be well reconstructed. (2)There are high requirements for reconstructed data. (3)Most data used to reconstructed are single temporal images.\\n\\n\\n\\nIn order to overcome these problems, a new multi temporal weighted aggregation method is proposed. Specifically, we adopt a multi-temporal iterative aggregation method for cloud pixels to reconstruct and a multi-temporal weighted aggregation method for cloud shadow pixels to reconstruct.\\n\\n\\n\\nFinally, the experiment proves that our method can quickly and accurately complete the cloud reconstruction, and under the effective uniform color strategy, a cloud- free image with accurate geometric position and uniform gray scale can be obtained.\\n\\n\\n\\nExperiments prove that the pixel reconstruction method proposed in this paper has achieved good cloud and cloud shadow pixel reconstruction effects in different types of ground objects.\\n\",\"PeriodicalId\":184819,\"journal\":{\"name\":\"Current Chinese Science\",\"volume\":\"164 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Chinese Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2174/2210298102666220616114622\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Chinese Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/2210298102666220616114622","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The existence of cloud pixels reduces the practicability of optical satellite remote sensing data.
Existing cloud reconstruction methods generally cannot solve the following problems:(1)Large-scale thick cloud cannot be well reconstructed. (2)There are high requirements for reconstructed data. (3)Most data used to reconstructed are single temporal images.
In order to overcome these problems, a new multi temporal weighted aggregation method is proposed. Specifically, we adopt a multi-temporal iterative aggregation method for cloud pixels to reconstruct and a multi-temporal weighted aggregation method for cloud shadow pixels to reconstruct.
Finally, the experiment proves that our method can quickly and accurately complete the cloud reconstruction, and under the effective uniform color strategy, a cloud- free image with accurate geometric position and uniform gray scale can be obtained.
Experiments prove that the pixel reconstruction method proposed in this paper has achieved good cloud and cloud shadow pixel reconstruction effects in different types of ground objects.