A Frequency Domain Approach to Registration of Aliased Images with Application to Super-resolution
By Patrick Vandewalle, Sabine Süsstrunk, Martin Vetterli. EURASIP Journal on Advances in Signal Processing, 2006
561 citations recorded by the source corpus.
Super-resolution algorithms reconstruct a high-resolution image from a set of low-resolution images of a scene. Precise alignment of the input images is an essential part of such algorithms. If the low-resolution images are undersampled and have aliasing artifacts, the performance of standard registration algorithms decreases. We propose a frequency domain technique to precisely register a set of aliased images, based on their low-frequency, aliasing-free part. A high-resolution image is then reconstructed using cubic interpolation. Our algorithm is compared to other algorithms in simulations and practical experiments using real aliased images. Both show very good visual results and prove the attractivity of our approach in the case of aliased input images. A possible application is to digital cameras where a set of rapidly acquired images can be used to recover a higher-resolution final image.
Subfields: Computer Vision and Pattern Recognition, Media Technology
View Paper: https://www.semanticscholar.org/paper/3e637fd7f01e3bd3d97b1ee0e5cd48de4d9b771e
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
- Michael Elad
- Peyman Milanfar
- Thomas Baltzer Moeslund
- Kamal Nasrollahi
- Lei Zhang
- Luc Van Gool
- Matan Protter
- Dacheng Tao
In Media Technology
- Thomas Baltzer Moeslund
- Kamal Nasrollahi
- Matan Protter
- Michael Elad
- Peyman Milanfar
- Hiroyuki Takeda
- Jelena Kovacevic
- Patrick Vandewalle
Citations in the corpus
- The Vienna LTE simulators - Enabling reproducibility in wireless communications research (2011, background): “In the past few years, several researchers have started to build up online resource databases in which simulation code and data are provided, see for example [4,5].”
- Generalizing the Nonlocal-Means to Super-Resolution Reconstruction (2009, background): “A wide variety of super resolution algorithms have been developed in the past 2 decades; we refer to [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26] as representatives of this vast literature.”
- Super-resolution: a comprehensive survey (2014, methodology): “[221], [267], [491], [511], [567] which have used a MAP method (Section 5.”
- Reproducible research in signal processing (2009, methodology): “It was developed on top of the reproducible research code from [23].”