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Proceedings Paper

Near-lossless compression algorithm for Bayer pattern color filter arrays
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Paper Abstract

In this contribution, we propose a near lossless compression algorithm for Color Filter Arrays (CFA) images. It allows higher compression ratio than any strictly lossless algorithm for the price of some small and controllable error. In our approach a structural transformation is applied first in order to pack the pixels of the same color in a structure appropriate for the subsequent compression algorithm. The transformed data is compressed with a modified version of the JPEG-LS algorithm. A nonlinear and adaptive error quantization function is embedded in the JPEG-LS algorithm after the fixed and context adaptive predictors. It is step-like and adapts to the base signal level in such a manner that higher error values are allowed for lighter parts with no visual quality loss. These higher error values are then suppressed by gamma correction applied during the image reconstruction stage. The algorithm can be adjusted for arbitrary pixel resolution, gamma value and tolerated error range. The compression performance of the proposed algorithm has been tested for real CFA raw data. The results are presented in terms of compression ratio versus reconstruction error and the visual quality of the reconstructed images is demonstrated as well.

Paper Details

Date Published: 23 February 2005
PDF: 12 pages
Proc. SPIE 5678, Digital Photography, (23 February 2005); doi: 10.1117/12.585788
Show Author Affiliations
Andriy Bazhyna, Tampere Univ. of Technology (Finland)
Atanas Gotchev, Tampere Univ. of Technology (Finland)
Karen Egiazarian, Tampere Univ. of Technology (Finland)

Published in SPIE Proceedings Vol. 5678:
Digital Photography
Nitin Sampat; Jeffrey M. DiCarlo; Ricardo J. Motta, Editor(s)

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