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Proceedings Paper

Motion-compensated spatial-temporal filtering for noisy CFA sequence
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Paper Abstract

Spatial-temporal filters have been widely used in video denoising module. The filters are commonly designed for monochromatic image. However, most digital video cameras use a color filter array (CFA) to get color sequence. We propose a recursive spatial-temporal filter using motion estimation (ME) and motion compensated prediction (MCP) for CFA sequence. In the proposed ME method, we obtain candidate motion vectors from CFA sequence through hypothetical luminance maps. With the estimated motion vectors, the accurate MCP is obtained from CFA sequence by weighted averaging, which is determined by spatial-temporal LMMSE. Then, the temporal filter combines estimated MCP and current pixel. This process is controlled by the motion detection value. After temporal filtering, the spatial filter is applied to the filtered current frame as a post-processing. Experimental results show that the proposed method achieves good denoising performance without motion blurring and acquires high visual quality.

Paper Details

Date Published: 2 February 2012
PDF: 8 pages
Proc. SPIE 8295, Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II, 82951D (2 February 2012); doi: 10.1117/12.907564
Show Author Affiliations
Min Seok Lee, Yonsei Univ. (Korea, Republic of)
Sang Wook Park, Yonsei Univ. (Korea, Republic of)
Moon Gi Kang, Yonsei Univ. (Korea, Republic of)


Published in SPIE Proceedings Vol. 8295:
Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II
Karen O. Egiazarian; John Recker; Guijin Wang; Sos S. Agaian; Atanas P. Gotchev, Editor(s)

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