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ICASSP
2010
IEEE

Empirical Type-i filter design for image interpolation

13 years 3 months ago
Empirical Type-i filter design for image interpolation
Empirical filter designs generalize relationships inferred from training data to effect realistic solutions that conform well to the human visual system. Complex algorithms involving multiple linear regressions produce optimal results, but a single zero-phase filter yields comparable image quality at a fraction of the computational load. We propose an algorithm that builds a single symmetrical linear filter based purely on collected training data. Such a filtering technique balances the tradeoff between performance and complexity. Previous implementations of zero-phase interpolation filters as well as other learning-based interpolating algorithms are analyzed and examined. The proposed algorithm utilizes a Type-I symmetrical filter, an improvement and alternative over previous work on Type-II empirically-based interpolating filters. Given image training patches, the work discusses the enforcement of our filter properties while simultaneously drawing information from the traini...
Karl S. Ni, Truong Q. Nguyen
Added 06 Dec 2010
Updated 06 Dec 2010
Type Conference
Year 2010
Where ICASSP
Authors Karl S. Ni, Truong Q. Nguyen
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