期刊名称：Oriental Journal of Computer Science and Technology
印刷版ISSN：0974-6471
出版年度：2010
卷号：3
期号：1
页码：13-20
语种：English
出版社：Oriental Scientific Publishing Company
摘要：In the present study Multispectral Image Processing (MIP) technique is applied on ASTER (Advance Spaceborne Thermal Emission and Reflection Radiometer) L1 B high resolution (15 m/ pixel) satellite data. A comprehensive spectral library of rice crop varieties : Hybrid-6129 (IET 18815), Pant Dhan-19 (IET 17544), Pusa Basmati-1 (IET-18990) and Pant Dhan-18 (IET-17920) has been developed with Blue (0.56 nm), Red (0.66 nm) and NIR (0.81 nm) spectral bands. The PCA (Principal Component Analysis) transformation with correlation matrix is applied for feature extraction to select an optimum subset of data in term of classification accuracy. Four PC (Principal Component) images selected for conventional spectral and integrated image classification. The integrated image Spectral/ NDVI (Normalized Difference Vegetation Index) is developed using Spectral and NDVI bands classified using ML (Maximum Likelihood) classifier. The conventional spectral classification accuracy for rice mapping is 79.5%, which improves up to 84.5% with Spectra/NDVI imagery data.
关键词：Multispectral Image Processing (MIP) ; NDVI ; PCA and ML (Maximum Likelihood)
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