This paper advocates an automatic technique to discover the optimum combination of three spectral features of a multispectral satellite image that enhance visualization of learned targets/objects. The method is an application-free, single-click user effort, spectrally and spatially balanced, fast-response, low-cost, information-based feature selector that comes to optimize maybe the most important problem in the computer-assisted work of the human operator: visualization of target areas. The new tools developed to assist image experts in their work need to be tailored to the new products offered by the sub-meter spatial resolution multispectral imaging sensors. The spectral bands of the satellite image are ranked using measures of mutual information-the minimum-redundancy-maximum-relevance mRMR criterion- and the top three are automatically displayed on screen. The evaluation of results is performed in terms of both quality (expert-driven visual analysis) and quantity (color metrics) and shows that this approach can become a powerful tool in support of image analysis operations.