16 October 2009 The study of noise filtering algorithm experiment on spatial domain and frequency domain of hyperspectral image
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Proceedings Volume 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining; 74924H (2009) https://doi.org/10.1117/12.838338
Event: International Symposium on Spatial Analysis, Spatial-temporal Data Modeling, and Data Mining, 2009, Wuhan, China
Abstract
The study of hyperspectral remote sensing data noise filtering algorithm is the key to improving data analysis. In this paper, to remove the stripe noise in spatial domain smooth filtering algorithm by row was used, while the wavelet threshold denoising method was used to filter random noise in spectral domain. The former was tested on actual data and got better results comparing with other moment matching methods. Not only was the stripe noise weakened well, but also the consistency of mean value curve was retained. Through the spectrum domain wavelet de-noising,the image is more smooth adopting soft threshold denoising method comparing with hard threshold denoising method, this proves that the soft threshold denoising filters the good effect. Experimental results demonstrated that the quality of the image was improved and the radiative feature was retained.
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Ling Han, Ling Han, Jing Wu, Jing Wu, } "The study of noise filtering algorithm experiment on spatial domain and frequency domain of hyperspectral image", Proc. SPIE 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 74924H (16 October 2009); doi: 10.1117/12.838338; https://doi.org/10.1117/12.838338
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