Improving Phase Correlation for Image Registration

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Author(s)
Gonzalez, Ruben
Griffith University Author(s)
Year published
2011
Metadata
Show full item recordAbstract
Phase correlation is a well-known technique for image registration that is robust to noise and operates in constant
time. Scale and rotation invariance can be achieved through means of a log-polar transformation. Unfortunately
this method has been historically shown to be unable to handle large rotation or scaling factors, making it
unsuitable for many image registration tasks. This paper presents a novel phase correlation based technique that
is shown to outperform the current state of the art image registration methods in terms of being able to recover
larger rotation and scaling factors and with reduced computational ...
View more >Phase correlation is a well-known technique for image registration that is robust to noise and operates in constant time. Scale and rotation invariance can be achieved through means of a log-polar transformation. Unfortunately this method has been historically shown to be unable to handle large rotation or scaling factors, making it unsuitable for many image registration tasks. This paper presents a novel phase correlation based technique that is shown to outperform the current state of the art image registration methods in terms of being able to recover larger rotation and scaling factors and with reduced computational requirements.
View less >
View more >Phase correlation is a well-known technique for image registration that is robust to noise and operates in constant time. Scale and rotation invariance can be achieved through means of a log-polar transformation. Unfortunately this method has been historically shown to be unable to handle large rotation or scaling factors, making it unsuitable for many image registration tasks. This paper presents a novel phase correlation based technique that is shown to outperform the current state of the art image registration methods in terms of being able to recover larger rotation and scaling factors and with reduced computational requirements.
View less >
Conference Title
Proceedings of Image and Vision Computing New Zealand 2011
Copyright Statement
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Subject
Computer Vision