摘要
A new method for image down-scaling using geostatistical interpolation or smoothing based on the Hopfield Neural Network(HNN) and zero semivariance value is introduced.The method utilises the smoothing effect of the semivariogram matching process to produce the smoothened sub-pixel multispectral(MS) image with smaller RMSEs in comparison with the bilinear interpolation.In fact,the zero semivariograms increase the spatial correlation between the adjacent sub-pixels of the superresolution image.Containing higher spatial correlation,the resulting super-resolution MS image has smaller RMSEs compared with the original coarse image.
A new method for image down-scaling using geostatistical interpolation or smoothing based on the Hopfield Neural Network（HNN） and zero semivariance value is introduced.The method utilises the smoothing effect of the semivariogram matching process to produce the smoothened sub-pixel multispectral（MS） image with smaller RMSEs in comparison with the bilinear interpolation.In fact,the zero semivariograms increase the spatial correlation between the adjacent sub-pixels of the superresolution image.Containing higher spatial correlation,the resulting super-resolution MS image has smaller RMSEs compared with the original coarse image.
出处
《遥感学报》
EI
CSCD
北大核心
2011年第3期640-644,共5页
NATIONAL REMOTE SENSING BULLETIN
