Abstract
In most digital cameras, Bayer color filter array (CFA) images are captured and demosaicing is generally carried out before compression. Recently, it was found that compression-first schemes outperform the conventional demosaicing-first schemes in terms of output image quality. An efficient prediction-based lossless compression scheme for Bayer CFA images is proposed in this paper. It exploits a context matching technique to rank the neighboring pixels when predicting a pixel, an adaptive color difference estimation scheme to remove the color spectral redundancy when handling red and blue samples, and an adaptive codeword generation technique to adjust the divisor of Rice code for encoding the prediction residues. Simulation results show that the proposed compression scheme can achieve a better compression performance than conventional lossless CFA image coding schemes.
Original language | English |
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Pages (from-to) | 134-144 |
Number of pages | 11 |
Journal | IEEE Transactions on Image Processing |
Volume | 17 |
Issue number | 2 |
DOIs | |
Publication status | Published - 1 Feb 2008 |
Keywords
- Bayer pattern
- Color filter array (CFA)
- Digital camera
- Entropy coding
- Image compression
ASJC Scopus subject areas
- Software
- Medicine(all)
- Computer Graphics and Computer-Aided Design