Hyperspectral and multispectral data fusion mission on hyperspectral imager suite (HISUI)

Hyperspectral imager suite (HISUI) is the Japanese next-generation earth-observing sensor composed of hyperspectral and multispectral imagers. Unmixing-based fusion of hyperspectral and multispectral data enables the production of high-spatial-resolution hyperspectral data. HISUI simulated imaging system combining two imagers was developed for verification experiments to investigate the feasibility and clarify the whole procedure of the hyperspectral and multispectral data fusion mission on HISUI. Airborne experiments are planned as simulation tests of HISUI higher-order products. The experimental results of the ground based observation showed the importance of the preprocessing and cross-calibration on the final quality of fused data, which contributes to the practical use of hyperspectral and multispectral data fusion.

[1]  H. Sebastian Seung,et al.  Learning the parts of objects by non-negative matrix factorization , 1999, Nature.

[2]  Russell C. Hardie,et al.  Application of the stochastic mixing model to hyperspectral resolution enhancement , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[3]  Graham D. Finlayson,et al.  Recovering Device Sensitivities with Quadratic Programming , 1998, Color Imaging Conference.

[4]  Sen Jia,et al.  Constrained Nonnegative Matrix Factorization for Hyperspectral Unmixing , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[5]  Yasuyuki Matsushita,et al.  High-resolution hyperspectral imaging via matrix factorization , 2011, CVPR 2011.

[6]  Naoto Yokoya,et al.  Cross-Calibration for Data Fusion of EO-1/Hyperion and Terra/ASTER , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[7]  Russell C. Hardie,et al.  MAP estimation for hyperspectral image resolution enhancement using an auxiliary sensor , 2004, IEEE Transactions on Image Processing.

[8]  Naoto Yokoya,et al.  Coupled Nonnegative Matrix Factorization Unmixing for Hyperspectral and Multispectral Data Fusion , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[9]  Hairong Qi,et al.  Endmember Extraction From Highly Mixed Data Using Minimum Volume Constrained Nonnegative Matrix Factorization , 2007, IEEE Transactions on Geoscience and Remote Sensing.