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A lossless compression scheme for Bayer color filter array images.

King-Hong Chung1, Yuk-Hee Chan

  • 1Centre for Multimedia Signal Processing, Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Hong Kong. king.hong.chung@polyu.edu.hk

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 14, 2008
PubMed
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A new compression-first method for Bayer color filter array (CFA) images improves image quality. This efficient lossless compression scheme outperforms traditional methods by predicting pixels and adapting color difference estimation.

Area of Science:

  • Digital Imaging
  • Image Compression
  • Computer Vision

Background:

  • Bayer color filter array (CFA) images are standard in digital cameras.
  • Demosaicing is typically performed before image compression.
  • Emerging compression-first methods show superior image quality compared to demosaicing-first approaches.

Purpose of the Study:

  • To propose an efficient prediction-based lossless compression scheme for Bayer CFA images.
  • To enhance image quality by optimizing the compression pipeline.
  • To improve upon existing lossless CFA image coding techniques.

Main Methods:

  • Utilizes context matching for neighboring pixel prediction.
  • Employs adaptive color difference estimation to reduce spectral redundancy in red and blue samples.

Related Experiment Videos

  • Incorporates adaptive codeword generation for Rice coding of prediction residues.

    • Main Results:

    • The proposed scheme achieves better compression performance than conventional lossless CFA image coding.
    • Demonstrates superior efficiency in compressing Bayer CFA images.
    • Validates the effectiveness of the prediction-based and adaptive techniques.

    Conclusions:

    • Compression-first schemes offer advantages for Bayer CFA image processing.
    • The proposed method provides an efficient and high-quality lossless compression solution.
    • This approach advances the field of digital image compression and processing.