Extension of phase correlation to subpixel registration

By Hassan Foroosh, Josiane Zerubia, Marc Berthod. IEEE Transactions on Image Processing, 2002

1,081 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Media Technology

View Paper: https://www.semanticscholar.org/paper/2c6c6d3c94322e9ff75ff2143f7028bfab2b3c5f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

In Media Technology

Citations in the corpus

Bispectrum Inversion with Application to Multireference Alignment (2017, background): “This problem occurs in a variety of applications in biology [1], [2], [3], [4], radar [5], [6], image registration and super-resolution [7], [8], [9], and has been the subject of recent theoretical analysis [10], [11].”
Automatic and Precise Orthorectification, Coregistration, and Subpixel Correlation of Satellite Images, Application to Ground Deformation Measurements (2007, background): “In [26], images to be correlated are supposed to be sampled with a sampling efficiency η = 1.”
Image Matching from Handcrafted to Deep Features: A Survey (2020, methodology): “…of converting the original images into another domain, such as phase correlation based on Fourier shift theorem (Reddy and Chatterji 1996; Liu et al. 2005; Chen et al. 1994; Takita et al. 2003; Foroosh et al. 2002), and Walsh transform-based methods (Lazaridis and Petrou 2006; Pan et al. 2008).”
Image registration methods: a survey (2003, neutral): “[61].”
Accurate indoor localization with zero start-up cost (2014, methodology): “We can then directly estimate and actively correct for this drift in real-time by applying phase correlation [10], a standard technique from computer graphics to estimate shifts between two (noisy) images by calculating their phase difference in the 2-D Fourier domain.”
A Frequency Domain Approach to Registration of Aliased Images with Application to Super-resolution (2006, background): “[21] showed that the signal power in the phase correlation corresponds to a polyphase transform of a filtered unit impulse.”
Neuropixels 2.0: A miniaturized high-density probe for stable, long-term brain recordings (2020, positive): “To achieve this objective, we use a standard correlation-based registration approach, similar to the approach used for 2p calcium imaging data (Foroosh et al., 2002; Pachitariu et al., 2017).”
Data Analysis WorkbeNch (DAWN) (2015, positive): “The main algorithm which was required for this work was the alignment of images, which was implemented using standard Fourier methods (Foroosh et al. , 2002).”
A review of multimodal image matching: Methods and applications (2021, methodology): “[407] extended early methods [405,406,408] based on multiscale log-Gabor [409] filtering and called their proposed method MLPC.”
A Vision-Based Sensor for Noncontact Structural Displacement Measurement (2015, methodology): “The interpolation technique is most commonly used subpixel approach, examples of which includes intensity interpolation, correlation coefficient curve-fitting or interpolation, phase correlation interpolation and the geometric methods [21–23].”