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Pre- and post-processing correlation filter data

Correlation filters have been shown to perform well for localization and classification tasks. In this paper, we investigate different techniques used to pre- and post-process the data to improve the correlation filter performance. In addition, we present an efficient method to use zero-mean, unit-norm test chips in a large test image. We compare the localization, classification, and recognition performance when we apply one or more of these methods.