1 May 2011 Adaptive autoregressive deinterlacing method
Jiaji Wu, Jin Huang, Gwanggil Jeon, Junsang Cho, Jechang Jeong, Licheng Jiao
Author Affiliations +
Abstract
This paper proposes a single-field deinterlacing method based on the autoregressive model and edge map. The new method interpolates missing pixels through estimating the deinterlaced covariance from the interlaced covariance, instead of estimating the edge orientations as previous intrafield deinterlaced methods (line average, edge-based line-average, direction-oriented interpolation, etc.) do. The proposed method adopts autoregressive mechanism, which considers mutual influence between the estimated missing pixels in a slip window. In addition, adding an edge map in our algorithm is used to reduce the computational complexity. The experimental results show that the proposed method outperformed the previous method in peak signal-to-noise ratio, and common artifacts (serration, line crawl, flicker, blurring, etc.) are significantly reduced.
©(2011) Society of Photo-Optical Instrumentation Engineers (SPIE)
Jiaji Wu, Jin Huang, Gwanggil Jeon, Junsang Cho, Jechang Jeong, and Licheng Jiao "Adaptive autoregressive deinterlacing method," Optical Engineering 50(5), 057001 (1 May 2011). https://doi.org/10.1117/1.3572125
Published: 1 May 2011
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CITATIONS
Cited by 11 scholarly publications and 3 patents.
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KEYWORDS
Autoregressive models

Image quality

Visualization

Computer aided design

Image processing

Sensors

Optical engineering

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