A Constrained Band Selection Method Based on Information Measures for Spectral Image Color Visualization

We present a new method for the visualization of spectral images, based on a selection of three relevant spectral channels to build a red–green–blue composite. Band selection is achieved by means of information measures at the first, second, and third orders. Irrelevant channels are preliminarily removed by means of a center-surround entropy comparison. A visualization-oriented spectrum segmentation based on the use of color matching functions allows for computational ease and adjustment of the natural rendering. Results from the proposed method are presented and objectively compared to four other dimensionality reduction techniques in terms of naturalness and informative content.