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Hyperspectral imaging system can obtain spectral and spatial information simultaneously with bandwidth to the level of 10 nm or even less. Therefore, hyperspectral remote sensing has the ability to detect some kinds of objects which can not be detected in wide-band remote sensing, making it becoming one of the hottest spots in remote sensing. In this study, under conditions with a fuzzy set of full constraints, Normalized Multi-Endmember Decomposition Method (NMEDM) for vegetation, water, and soil was proposed to reconstruct hyperspectral data using a large number of high-quality multispectral data and auxiliary spectral library data. This study considered spatial and temporal variation and decreased the calculation time required to reconstruct the hyper-spectral data. The results of spectral reconstruction based on NMEDM showed that the reconstructed data has good qualities and certain applications, which makes it possible to carry out spectral features identification. This method also extends the application of depth and breadth of remote sensing data, helping to explore the law between multispectral and hyperspectral data

THE STUDY OF SPECTRUM RECONSTRUCTION BASED ON FUZZY SET FULL CONSTRAINT AND MULTIENDMEMBER DECOMPOSITION