Abstract
Recent years have brought a quick decay in prize of hyperspectral imagery equipment. As a consequence, new applications have appeared, a relevant example being the analysis of agro-food materials. Such applications need to be grounded on dedicated image processing operators, which fully accomplish with (and exploit) the characteristics of hyperspectral imagery. In this regard, we study the quantitative comparison of spectra, which can be further used to produce a variety of image processing operators. Specifically, we propose the use of Baddeley’s Delta metric for the comparison of spectra. Our method has theoretical advantages over classical bandwise comparison measures, which are often inconsistent with human perception of dissimilarity between spectra. Our proposal is put to the test in the context of local contrast computation, with application to item segmentation of in-laboratory imagery.
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