Perceptual display strategies of hyperspectral imagery based on PCA and ICA

Hongqin Zhang; David W. Messinger; Ethan D. Montag

doi:10.1117/12.665696

4 May 2006 Perceptual display strategies of hyperspectral imagery based on PCA and ICA

Hongqin Zhang, David W. Messinger, Ethan D. Montag

Proceedings Volume 6233, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII; 62330X (2006) https://doi.org/10.1117/12.665696
Event: Defense and Security Symposium, 2006, Orlando (Kissimmee), Florida, United States

Abstract

This study investigated appropriate methodologies for displaying hyperspectral imagery based on knowledge of human color vision as applied to Hyperion and AVIRIS data. Principal Component Analysis (PCA) and Independent Component Analysis (ICA) were used to reduce the data dimensionality in order to make the data more amenable to visualization in three-dimensional color space. In addition, these two methods were chosen because of their underlying relationships to the opponent color model of human color perception. PCA and ICA-based visualization strategies were then explored by mapping the first three PCs or ICs to several opponent color spaces including CIELAB, HSV, YCrCb, and YUV. The gray world assumption, which states that given an image with sufficient amount of color variations, the average color should be gray, was used to set the mapping origins. The rendered images are well color balanced and can offer a first look capability or initial classification for a wide variety of spectral scenes.

Citation Download Citation

Hongqin Zhang, David W. Messinger, and Ethan D. Montag "Perceptual display strategies of hyperspectral imagery based on PCA and ICA", Proc. SPIE 6233, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII, 62330X (4 May 2006); https://doi.org/10.1117/12.665696

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