Zero-aliasing correlation filters

Joseph A. Fernandez, B. Kumar
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引用次数: 14

Abstract

Traditional correlation filters are designed and implemented via the frequency domain, where the correlation of two signals may be computed efficiently. However, when the discrete Fourier transform (DFT) of length N is used, multiplication in the frequency domain results in an N-point circular correlation, rather than a linear correlation. The resulting correlation filter output is therefore corrupted by the aliasing effects of circular correlation. One solution is to design and implement the correlation filter directly in the space domain. However, this is more computationally intense. Recent literature has discussed ways in which to minimize circular correlation effects, but the effects are not completely removed. We propose a new frequency domain method for completely eliminating circular correlation effects when designing correlation filters. We demonstrate this idea with the well-known minimum average correlation energy (MACE) filter and show how the reformulated MACE filter in the frequency domain outperforms the original formulation of the MACE filter.
零混叠相关滤波器
传统的相关滤波器是通过频域设计和实现的,可以有效地计算两个信号的相关性。然而,当使用长度为N的离散傅里叶变换(DFT)时,频域中的乘法会产生N点圆相关,而不是线性相关。由此产生的相关滤波器输出因此被圆形相关的混叠效应所破坏。一种解决方案是直接在空间域中设计和实现相关滤波器。然而,这是更密集的计算。最近的文献讨论了最小化循环相关效应的方法,但这种效应并没有完全消除。在设计相关滤波器时,我们提出了一种新的频域方法来完全消除圆形相关效应。我们用著名的最小平均相关能(MACE)滤波器证明了这一思想,并展示了在频域重新表述的MACE滤波器如何优于原MACE滤波器的表述。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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