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Perceptual color image coding with JPEG2000
1School of Electrical and Computer Engineering,Royal Melbourne Institute of Technology, Australia. damian.tan@rmit.edu.au
Summary
A new perceptual color image coder (PCIC) optimizes image quality by using a vision model. This method significantly improves visual fidelity at lower bitrates compared to standard JPEG2000 coders.
Area of Science:
- Digital image processing
- Computer vision
- Image compression
Background:
- JPEG2000 is a standard for image compression.
- Existing distortion metrics like MSE and Cvis do not fully capture human visual perception.
- Color image coding requires advanced methods to maintain visual quality.
Purpose of the Study:
- To introduce a perceptual color image coder (PCIC) for the YCbCr color space.
- To enhance visual quality in coded images using a vision model-based perceptual distortion metric (PDM).
- To optimize rate-distortion (R-D) performance for superior image compression.
Main Methods:
- Developed a PCIC within the JPEG2000 framework.
- Extended a monochromatic multichannel vision model for color image coding.
- Employed a PDM for R-D optimization, approximating perceived error.
- Conducted subjective tests with 30 viewers for quality assessment.
Main Results:
- The PCIC demonstrated superior picture quality at low to intermediate bitrates.
- Performance was compared against JPEG2000 coders using MSE and Cvis distortion measures.
- The PDM effectively approximated perceived error for better visual quality.
Conclusions:
- The PCIC offers enhanced visual quality for color image compression.
- Vision model-based distortion metrics are crucial for perceptually optimized coding.
- The proposed method outperforms traditional metrics in subjective evaluations.
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