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15 August 2011 Space-borne hyperspectral remote sensing imagery noise eliminating based on CFFT self-adapted by optimal SNR
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Proceedings Volume 8203, Remote Sensing of the Environment: The 17th China Conference on Remote Sensing; 82030N (2011) https://doi.org/10.1117/12.910400
Event: Seventeenth China Symposium on Remote Sensing, 2010, Hangzhou, China
Abstract
Space-borne hyperspectral remote sensing imagery, supplying both spatial and spectral information for quantitative remote sensing monitoring, is easily polluted by noises from atmosphere, terrain etc. Based on spectral continuum removing and recovering, traditional fast Fourier Transform (FFT) was extended to Continuum Fast Fourier Transform (CFFT) to separate noise from target information in frequency domain (FD). Thus, low-pass filter for reserving useful information was designed for eliminating noise, with its cut-off frequency selected self-adaptively by optimal signal-tonoise ratio (SNR). Hyperion hyperspectral imageries of Beijing and Xinjiang China were singled out for noise removing to validate the filtering ability of the Continuum Fast Fourier Transform self-adapted by Optimal Signal-noise Ratio(CFFTOSNR) method with qualitative description and quantificational indexs, including mean, variance, entropy, definition and SNR etc. Experiment result shows that CFFTOSNR does well in reducing the gauss white noises in spectral domain and stripe and band-subtracting noise in spatial domain respectively, while the quantificational indexs of filtered imagery are all improved, with entropy of post-processed image obviously increased by 5 db.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Qingjie Liu, Qizhong Lin, Liming Wang, Qinjun Wang, and Fengxian Miao "Space-borne hyperspectral remote sensing imagery noise eliminating based on CFFT self-adapted by optimal SNR", Proc. SPIE 8203, Remote Sensing of the Environment: The 17th China Conference on Remote Sensing, 82030N (15 August 2011); https://doi.org/10.1117/12.910400
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