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Proceedings Paper

Estimation of color filter array data from JPEG images for improved demosaicking
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Paper Abstract

On-camera demosaicking algorithms are necessarily simple and therefore do not yield the best possible images. However, off-camera demosaicking algorithms face the additional challenge that the data has been compressed and therefore corrupted by quantization noise. We propose a method to estimate the original color filter array (CFA) data from JPEG-compressed images so that more sophisticated (and better) demosaicking schemes can be applied to get higher-quality images. The JPEG image formation process, including simple demosaicking, color space transformation, chrominance channel decimation and DCT, is modeled as a series of matrix operations followed by quantization on the CFA data, which is estimated by least squares. An iterative method is used to conserve memory and speed computation. Our experiments show that the mean square error (MSE) with respect to the original CFA data is reduced significantly using our algorithm, compared to that of unprocessed JPEG and deblocked JPEG data.

Paper Details

Date Published: 2 February 2006
PDF: 5 pages
Proc. SPIE 6065, Computational Imaging IV, 606510 (2 February 2006); doi: 10.1117/12.657899
Show Author Affiliations
Wei Feng, Auburn Univ. (United States)
Stanley J. Reeves, Auburn Univ. (United States)


Published in SPIE Proceedings Vol. 6065:
Computational Imaging IV
Charles A. Bouman; Eric L. Miller; Ilya Pollak, Editor(s)

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