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== Introduction == | == Introduction == | ||
In this project, we applied several machine learning algorithms like L3 (Local, Linear and Learned) and a neural network based model to find the appropriate mapping from NIR to RGB visible spectrum which human eyes are more sensitive to. We evaluate the results based on the CIELAB delta E metric for measuring difference in human perception level and the RMSE metric for quantitatively measuring pixels differences across image. | In this project, we applied several machine learning algorithms like L3 (Local, Linear and Learned) and a neural network based model to find the appropriate mapping from NIR to RGB visible spectrum which human eyes are more sensitive to. We evaluate the results based on the CIELAB delta E metric for measuring difference in human perception level and the RMSE metric for quantitatively measuring pixels differences across image. | ||
Revision as of 23:39, 14 December 2018
Introduction
In this project, we applied several machine learning algorithms like L3 (Local, Linear and Learned) and a neural network based model to find the appropriate mapping from NIR to RGB visible spectrum which human eyes are more sensitive to. We evaluate the results based on the CIELAB delta E metric for measuring difference in human perception level and the RMSE metric for quantitatively measuring pixels differences across image.
Background
L3 Method
CNN Method
Results
Conclusions
Appendix I
Appendix II
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