Image smoothing of multispectral imagery based on the HNN and geo-statistics

Nguyen Quang Minh

doi:10.11834/jrs.20110315

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Image smoothing of multispectral imagery based on the HNN and geo-statistics
Image smoothing of multispectral imagery based on the HNN and geo-statistics
2011年15卷第3期页码：640-644
纸质出版日期： 2011 ，
DOI： 10.11834/jrs.20110315

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[1]Nguyen Quang Minh.Image smoothing of multispectral imagery based on the HNN and geo-statistics[J].遥感学报,2011,15(03):640-644.

Image smoothing of multispectral imagery based on the HNN and geo-statistics[J]. Journal of Remote Sensing, 2011,15(3):640-644.
[1]Nguyen Quang Minh.Image smoothing of multispectral imagery based on the HNN and geo-statistics[J].遥感学报,2011,15(03):640-644. DOI： 10.11834/jrs.20110315.

Image smoothing of multispectral imagery based on the HNN and geo-statistics[J]. Journal of Remote Sensing, 2011,15(3):640-644. DOI： 10.11834/jrs.20110315.

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.

Abstract

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.

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