Mr. Sebastian Lenke Profile

Sebastian Lenke

Scientific Assistant at Univ Dortmund

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Proceedings Article | 3 March 2008 Paper

Classification based polynomial image interpolation

Sebastian Lenke, Hartmut Schröder

Proceedings Volume 6812, 681214 (2008) https://doi.org/10.1117/12.766245

KEYWORDS: Digital filtering, Linear filtering, Image interpolation, Image classification, Optical filters, Image quality, Image filtering, Signal attenuation, Image resolution, Motion estimation

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Due to the fast migration of high resolution displays for home and office environments there is a strong demand for high quality picture scaling. This is caused on the one hand by large picture sizes and on the other hand due to an enhanced visibility of picture artifacts on these displays [1]. There are many proposals for an enhanced spatial interpolation adaptively matched to picture contents like e.g. edges. The drawback of these approaches is the normally integer and often limited interpolation factor. In order to achieve rational factors there exist combinations of adaptive and non adaptive linear filters, but due to the non adaptive step the overall quality is notably limited. We present in this paper a content adaptive polyphase interpolation method which uses "offline" trained filter coefficients and an "online" linear filtering depending on a simple classification of the input situation. Furthermore we present a new approach to a content adaptive interpolation polynomial, which allows arbitrary polyphase interpolation factors at runtime and further improves the overall interpolation quality. The main goal of our new approach is to optimize interpolation quality by adapting higher order polynomials directly to the image content. In addition we derive filter constraints for enhanced picture quality. Furthermore we extend the classification based filtering to the temporal dimension in order to use it for an intermediate image interpolation.

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