Automatic Whole-Spectrum Matching
نویسندگان
چکیده
In many space science applications, there is a need for the ability to match spectra of unknown objects against a reference spectral database. Whole-spectrum matching has been shown to perform this task effectively, but its performance is strongly linked to end-user choices, as well as specific characteristics of the dataset involved. Conventionally, the task of tuning the matching algorithm falls to the user, a time-consuming and often subjective undertaking. In this paper, we generalize these tunable choices within a preprocessing and matching framework, making this tuning process amenable to automated optimization methods. Our novel method dramatically reduces the burden on the user and results in improved matching accuracy.
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تاریخ انتشار 2015