Motion estimation from noisy image sequences using new frequency weighting functions
Küçük Resim Yok
Tarih
2019
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Maltepe Üniversitesi
Erişim Hakkı
CC0 1.0 Universal
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess
Özet
Motion estimation is a signal-matching technique. It is a key component of target tracking, medical imaging, video compression, and many other systems. This paper presents a four new estimators for frame-to-frame image motion estimation. The estimators of interest are the ROTH impulse response, the smoothed coherence transform (SCOT), the maximum likelihood (ML) and the Wiener estimators. These are all referred to as Generalized Cross-Correlation (GCC)-estimators. These estimators are based on the cross-correlation of the received images and various weighting functions are used to prefilter the received images before crosscorrelation. As the performances of the GCC-estimators are considerably degraded by the signal-to-noise ratio (SNR) level, this factor has been taken as a prime factor in benchmarking the different GCC-estimators. For robust motion estimation it has been found that the GCC-Wiener is particularly suited to this purpose. The accuracy of the estimators is also discussed.
Açıklama
Anahtar Kelimeler
Motion estimation, Whitening function, Noisy image sequences, GCC-estimators
Kaynak
International Conference of Mathematical Sciences (ICMS 2019)
WoS Q Değeri
Scopus Q Değeri
Cilt
Sayı
Künye
El Mehdi, İ. A. (2019). Motion estimation from noisy image sequences using new frequency weighting functions. International Conference of Mathematical Sciences (ICMS 2019). s. 149.
