Abstract
Several correlation filters are derived to improve pattern recognition of a noisy target embedded into nonoverlapping background, when the input image is degraded with a linear system. With the help of computer simulation we analyze and compare the performance of various correlation based methods for reliable detection and localization of objects in blurred and noisy images.
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Ramos-Michel, E.M., Kober, V. (2006). Correlation Filters for Detection and Localization of Objects in Degraded Images. In: Martínez-Trinidad, J.F., Carrasco Ochoa, J.A., Kittler, J. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2006. Lecture Notes in Computer Science, vol 4225. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11892755_47
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DOI: https://doi.org/10.1007/11892755_47
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