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Classified JPEG coding of mixed document images for printing
Summary
This study introduces a modified JPEG coder for mixed documents, enhancing perceptual quality for printing. The region-adaptive approach improves compression by classifying document areas, ensuring baseline compliance.
Area of Science:
- Computer Vision
- Image Processing
- Digital Compression
Background:
- Standard JPEG compression struggles with mixed documents (text, images, graphics).
- Perceptual quality is crucial for printed mixed-content documents.
- Existing methods lack region-specific optimization for mixed documents.
Discussion:
- A novel, region-adaptive JPEG coder is proposed for mixed documents.
- The coder utilizes classified thresholding, maintaining baseline JPEG standard compliance.
- A computationally efficient classification algorithm is integral to the method.
Key Insights:
- The modified JPEG coder achieves superior perceptual quality over the standard JPEG coder.
- Region-adaptivity effectively leverages distinct perceptual zones within mixed documents.
- The classification algorithm enables efficient processing without compromising quality.
Outlook:
- Potential for improved image compression in digital printing workflows.
- Further research into adaptive compression for diverse document types.
- Integration with printing pipelines for enhanced visual fidelity.
