A Computationally Efficient Super-Resolution Algorithm for Video Processing Using Partition Filters
Document Type
Article
Publication Date
5-2007
Publication Source
IEEE Transactions on Circuits and Systems for Video Technology
Abstract
We propose a computationally efficient super-resolution (SR) algorithm to produce high-resolution videofrom low-resolution (LR) video using partition-based weighted sum (PWS) filters. First, subpixel motion parameters are estimated from the LR video frames. These are used to position the observed LR pixels into a high-resolution (HR) grid. Finally, PWS filters are employed to simultaneously perform nonuniform interpolation (to fully populate the HR grid) and perform deconvolution of the system point spread function. The PWS filters operate with a moving window. At each window location, the output is formedusing a weighted sum of the present pixels within the window. The weights are selected from a filterbank based on the configuration of missing pixels in the window and the intensity structure of the present pixels. We present an algorithm for applying the PWS SR filters to video that is computationally efficient and suitable for parallel implementation. A number of experimental results are presented to demonstrate the efficacy of the proposed algorithm in comparison to several previously published methods. A detailed computational analysis of the partition-based SR filters is also presented.
Inclusive pages
621-634
ISBN/ISSN
1051-8215
Publisher
IEEE: Institute of Electrical and Electronics Engineers
Volume
17
Peer Reviewed
yes
Issue
5
eCommons Citation
Narayanan, Balaji; Hardie, Russell C.; Barner, Kenneth E.; and Shao, Min, "A Computationally Efficient Super-Resolution Algorithm for Video Processing Using Partition Filters" (2007). Electrical and Computer Engineering Faculty Publications. 65.
https://ecommons.udayton.edu/ece_fac_pub/65
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