Evaluation of Noise Removal of Radiance Data on Onboard Data Compression of Hyperspectral Imagery
نویسندگان
چکیده
This paper evaluates the impact of removing random noise of radiance data using a spectral-spatial smoothing approach on data compression onboard a hyperspectral satellite. A datacube acquired using a Short Wave Infrared Full Spectrum Imager II for target detection application of hyperspectral data was tested. The impact was evaluated using both the statistical based measures and a remote sensing application. The evaluation results show that compression on radiance data after removal of random noise produces better reconstruction fidelity and much higher evaluation scores for the remote sensing application than compression on radiance data without removal of random noise. The evaluation results indicate that random noise of radiance data should be removed before compression, if data compression is applied on radiance data onboard. Key-Words: Hyperspectral imagery, onboard data compression, noise removal, evaluation of impact
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