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Multiscale probabilistic dithering for suppressing contour artifacts in digital images
Sitaram Bhagavathy1, Joan Llach, Jiefu Zhai
1Signal Acquisition and Processing Group, Thomson Corporate Research, Princeton, NJ 08540, USA. sitaram.bhagavathy@thomson.net
Summary
This study introduces a novel method to reduce contour artifacts in digital images caused by color quantization. By analyzing pixel neighborhoods and probabilistically dithering colors, it effectively breaks down false contours, enhancing image quality.
Area of Science:
- Digital Image Processing
- Computer Vision
- Color Science
Background:
- Color quantization in digital images can lead to undesirable contour artifacts.
- These false contours degrade the visual quality of images, particularly in areas with smooth color gradients.
Purpose of the Study:
- To develop and present a method for effectively reducing the visibility of contour artifacts.
- To ensure that artifact-free regions of an image remain unaffected by the proposed method.
Main Methods:
- A multiscale analysis is performed on the neighborhood of each pixel.
- The presence and scale of contour artifacts are determined.
- Probabilistic dithering (perturbation) of pixel colors is applied to break down false contours.
Main Results:
- The proposed method successfully reduces the visibility of contour artifacts.
- The technique can be applied at the same bit depth as the input image or at higher bit depths.
- Artifact detection ensures that genuine image regions are preserved.
Conclusions:
- The developed method offers an effective solution for mitigating contour artifacts in digital images.
- This approach enhances image fidelity by reducing quantization-induced distortions without affecting uncompromised image areas.
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