Comparative Analysis of Zero Aliasing Logarithmic mapped Optimal Trade-Off Correlation Filter

摘要

Correlation filters are a well established means for target recognition tasks. However, the unintentional effect of circular correlation has a negative influence on the performance of correlation filters as they are implemented in frequency domain. The effects of aliasing are minimized by introducing zero aliasing constraints in the template and test image. In this paper, the comparative analysis of logarithmic zero aliasing optimal trade off correlation filters has been carried out for different types of target distortions. The zero aliasing Maximum Average Correlation Height (MACH) filter has been identified as the best choice based on our research for achieving enhanced results in the presence of any type of variance which are discussed in results section. The reformulation of the MACH expressions with zero aliasing has been made to demonstrate the achievable enhancement to the logarithmic MACH filter in target detection applications.