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《Remote Sensing Technology and Application》 2012-01
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SNR Estimation for Remote Sensing Images based on Edge Extraction and Spatial Dimension Decorrelation

Zhu Bo,Wang Xinhong,Tang Lingli,Li Chuanrong(Academy of Opto-Electronics,Chinese Academy of Sciences,Beijing 100094,China)  
It is known that the same or even similar spectrum features and quantized data exist in the same type of the surface features in an image by analyzing the spectrum and surface features.And there are many correlations between signals in homogeneous regions.But the noises are random,independent and de-correlation.It means that the spectrum reflecting values in homogeneous regions of a remote sensing Image are correlating.The noises can be separated from the values,if the real signals can be estimated based on the correlation.The paper presents a method,called extracting edge and spatial dimension correlation(EESDD),to estimate the standard deviation(SD) of signals or signal-to-noise ratio(SNR).The method is full use of the surface features to extract the edges,and estimate the SD or SNR by the correlation of signals in homogeneous regions.EESDD can be applied in estimating noise not only for a single wavelength image,but also for a hyperspectral image.And this method is used for the homogeneous and inhomogeneous regions,too.Comparing to the local mean standard deviation(LMSD) and the edge-extracted local mean standard deviation(EE-LMSD) in Hyperion data with different scene contents,the result of EESDD is far better than those of LMSD and EE-LMSD.
【Fund】: 国家863计划项目(2008AA121805);; 广西科学研究与技术开发计划项目(桂科攻0993002-2)
【CateGory Index】: TP751
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