A trained filter de-interlacer based on complex classification

Dmitry Znamenskiy; Marco Kruse

doi:10.1117/12.805906

19 January 2009 A trained filter de-interlacer based on complex classification

Dmitry Znamenskiy, Marco Kruse

Proceedings Volume 7257, Visual Communications and Image Processing 2009; 72571C (2009) https://doi.org/10.1117/12.805906
Event: IS&T/SPIE Electronic Imaging, 2009, San Jose, California, United States

Abstract

A novel trained filter based scheme for video de-interlacing is proposed and described in detail. This scheme uses different classifiers, called error functions, on the input, and mixes several sub-de-interlacers depending on them. The approach differs from the earlier works in this area due to focus on more complex classification rather than on complex sub-de-interlacers. The proposed scheme is flexible and allows various combinations of error functions with sub-de-interlacers. In this article we describe a test implementation of this concept with five different sub-de-interlacers and five error functions composing a spatial-temporal de-interlacing method. The description of the test implementation is supported by simulations where we evaluate the contribution of different sub-de-interlacers and error function to output de-interlacing quality.

Citation Download Citation

Dmitry Znamenskiy and Marco Kruse "A trained filter de-interlacer based on complex classification", Proc. SPIE 7257, Visual Communications and Image Processing 2009, 72571C (19 January 2009); https://doi.org/10.1117/12.805906

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KEYWORDS

Video

Linear filtering

Digital filtering

Visibility

Detection and tracking algorithms

Diamond

Flat panel displays

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