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This paper examines the definitions of contrast as variously defined and used in target acquisition. A general definition of contrast is a difference normalized for significance. It is proposed that the difference be described as a signature metric and the normalization factor, which is usually in the same units as the signature metric, be characterized as a contrast reference. The various existing definitions are shown to be consistent with this definition. Common signature metrics are examined across a variety of target conditions. A new signature metric and contrast reference are proposed and examined. The development and use of contrast as a metric in image quality assessment is reviewed. Modern research methods involving image quality and local contrast are also examined and shown to be consistent with the general concept of contrast. We introduce local Michelson contrast, local Maximum Michelson contrast, natural scene statistics (NSS), and local Weber contrast. These local contrast measures produce a feature space that must be analyzed. We examine mean shift analysis as a means for analyzing those feature spaces. We apply mean shift analysis to imagery and discuss its benefits and shortcomings. We propose future paths forward for metric development in assessing target acquisition performance.
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