29 December 2008 Quantitative improvement in geology interpretation from remotely sensed data by denoising the haze
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Proceedings Volume 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA); 72851B (2008) https://doi.org/10.1117/12.815896
Event: International Conference on Earth Observation Data Processing and Analysis, 2008, Wuhan, China
Abstract
The development of remote geological interpretation technology is booming during recent years. However, there is a significant obstacle for extracting geology information from remote sensing imagery--the presence of clouds and their shadows. Diverse techniques have been proposed including different algorithms such as filtering algorithm and multi-temporal cloud removing algorithm to solve the problem. This paper presents a modified solution to denoise the haze, based on ETM+ imagery. First of all, wavelet transform is applied to Band1, Band2 and Band3 imagery to determine the clear region and different levels of cloud regions. Then all pixels of the ETM+ imagery are classified to specific cover types after the cluster analysis of band4, Band5 and Band7. At last, the mean reflectance matching is performed in the first three bands separately according to different cover types in both clear region and cloud region. Above all, the method is implemented by IDL. The results show that this modified method not only can quantitatively determine the cloud area but also can remove cloud from imagery efficiently. Moreover, compared with the homomorphic filtering method, the experiment results of the proposed method is much more satisfying in Geology Interpretation.
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Hai-ping Yang, Hai-ping Yang, Xiu-guo Liu, Xiu-guo Liu, Fu-jiang Liu, Fu-jiang Liu, Guo-ping Wu, Guo-ping Wu, Jin-ping Shi, Jin-ping Shi, Lin-lu Mei, Lin-lu Mei, } "Quantitative improvement in geology interpretation from remotely sensed data by denoising the haze", Proc. SPIE 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 72851B (29 December 2008); doi: 10.1117/12.815896; https://doi.org/10.1117/12.815896
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