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发表刊物：IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING

关键字：Global radiometric block adjustment,multitemporal satellite images, multivariate alteration detection(MAD), radiometric normalization.

摘要：Determining appropriate master images, reducing radiometric error accumulation, and eliminating outliers from the cloud, water, and land changes, are three main issues in radiometric normalization of multitemporal high-resolution satellite images (HRSI) during mosaicking. However, these three issues have not been simultaneously considered by the existing methods. This article presents a comprehensive radiometric normalization method for multitemporal HRSI using a radiometric block adjustment without master images. Pseudoinvariant features (PIFs) extracted from image pairs using the iteratively reweighted multivariate alteration detection are used as the corresponding pixel observations and organized to form radiometric tie points according to the corresponding horizontal space coordinates. Radiometric error equations are subsequently constructed, and the linear radiometric transformation parameters are solved by a global adjustment. The time-invariant PIFs generally represent the true corresponding features and naturally avoid the cloud, water, and land changes, which can eliminate the effects of outliers. Furthermore, the pixel values of tie points calculated from the weighted average of the corresponding pixel observations are used as virtual radiometric control points to eliminate the dependency on master images. Moreover, a global optimum can be achieved by the global adjustment, effectively overcoming the error accumulation, which is severe in large datasets. Four groups of HRSI datasets from various satellites are used to validate the performance of the proposed method. Experimental results demonstrate that the proposed method outperforms two state-of-the-art methods and has good applicability and stability, considering both visual effects and quantitative performance.

合写作者：Tao Ke,Jianan He,Ke Xi,Kaijun Yang

通讯作者：Pengjie Tao

卷号：13

页面范围：6029-6043

是否译文：否

发表时间：2020-10-31

收录刊物：SCI、EI