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Improved LLM Methods Using Linear Regression

Permanent link
https://hdl.handle.net/10037/15589
DOI
https://doi.org/10.1109/IGARSS.2017.8128212
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accepted manuscript (PDF)
Date
2017-12-04
Type
Journal article
Peer reviewed

Author
Zhao, Zihang; Lang, Wenhui; Doulgeris, Anthony Paul; Chen, Lu
Abstract
This paper is focused on investigations of the improved correction of the effect of variation in incidence angle on ScanSAR data. Conventional correction methods (such as LLM, locally linear mapping) typically assume that each target class has a similarity distribution in the middle of the image. The objectives of this study are to extend the correction algorithm to full swath width without any assumptions. For a target class only distributed on one or both sides of the image, interpolation or extrapolation of the confidence interval is realized using the linear regression technique based on the exponential model. The position of the reference band is then determined and the correction is performed. Experiments were performed on ENVISAT ASAR and RADARSAT-2 ScanSAR data. The results show the effectiveness of the proposed method.
Description
Accepted manuscript file. Publisher's version available at: http://dx.doi.org/10.1109/IGARSS.2017.8128212
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Zhao, Zihang, Lang, Wenhui, Doulgeris, Anthony Paul, Chen, Lu. (2017) Improved LLM Methods Using Linear Regression. Proceedings of 2017 IEEE International Geoscience and Remote Sensing Symposium (5350-5353). 10.1109/IGARSS.2017.8128212
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