Polyphase interpretation of empirical image interpolation
Name
Ni-2009-Polyphase interpretation of empirical image interpolation.pdf
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512.69 KB
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Adobe PDF
Checksum (MD5)
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Author(s)
Ni, Karl S.
Nguyen, Truong Q.
Date Issued
May 2009
Journal
IEEE International Conference on Acoustics, Speech and Signal Processing, 2009. ICASSP 2009
Publisher
Institute of Electrical and Electronics Engineers
Citation
Ni, K., and T.Q. Nguyen. “Polyphase interpretation of empirical image interpolation.” Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on. 2009. 837-840. © 2009 IEEE.
Version
Final published version
Abstract
We observe several characteristics of empirical image interpolating algorithms and contribute four novel concepts and claims. First, we interpret well-known classification-based filtering algorithms in terms of their polyphase components. We examine the underlying principles behind the various fixed-scale linear interpolating kernels. Second, we conceptually extend the properties of the multiple filters to two dimensions to analyze frequency domain characteristics common to all empirically-designed interpolating filters. Third, we propose a general linear filter for image interpolation, which uses a universal magnitude response and zero-phase. Finally, the proposed filter is further generalized to support arbitrary scaling factors. We claim that at any scaling factor, the proposed algorithm yields low-complexity at a minimal loss of high image-quality with the ability to interpolate diverse image content.
MIT Department
Lincoln Laboratory
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1109/ICASSP.2009.4959714
