Hyperspectral image processing: a direct image simplification method

Christopher A. Neylan; Tyler Rush; Angel Gutierrez; Stefan A. Robila

doi:10.1117/12.780080

11 April 2008 Hyperspectral image processing: a direct image simplification method

Christopher A. Neylan, Tyler Rush, Angel Gutierrez, Stefan A. Robila

Proceedings Volume 6966, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV; 69661Y (2008) https://doi.org/10.1117/12.780080
Event: SPIE Defense and Security Symposium, 2008, Orlando, Florida, United States

Abstract

We describe a novel approach to produce color composite images from hyperspectral data using weighted spectra averages. The weighted average is based on a sequence of numbers (weights) selected using pixel value information and interband distance. Separate sequences of weights are generated for each of the three color bands forming the color composite image. Tuning of the weighting parameters and emphasis on different spectral areas allows for emphasis of one or other feature in the image. The produced image is a distinct approach from a regular color composite result, since all the bands provide information to the final result. The algorithm was implemented in high level programming language and provided with a user friendly graphical interface. The current design allows for stand-alone usage or for further modifications into a real time visualization module. Experimental results show that the weighted color composition is an extremely fast visualization tool.

Citation Download Citation

Christopher A. Neylan, Tyler Rush, Angel Gutierrez, and Stefan A. Robila "Hyperspectral image processing: a direct image simplification method", Proc. SPIE 6966, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV, 69661Y (11 April 2008); https://doi.org/10.1117/12.780080

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