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Published on: April 16, 2010
Efficient improvements on the BDND filtering algorithm for the removal of high-density impulse noise
Iyad F Jafar1, Rami A AlNa'mneh, Khalid A Darabkh
1Computer Engineering Department, University of Jordan, Amman 1192, Jordan. iyad.jafar@ju.edu.jo
Summary
Switching median filters improve impulse noise removal. This study enhances the Boundary Discriminative Noise Detection (BDND) algorithm, resulting in sharper images compared to the original BDND method.
Area of Science:
- Image processing
- Digital signal processing
Background:
- Standard median filters struggle with impulse noise.
- Switching median filters offer superior noise removal by selectively filtering pixels.
- The Boundary Discriminative Noise Detection (BDND) algorithm is a notable switching median filter but has performance limitations.
Purpose of the Study:
- To address performance degradation in the BDND algorithm's filtering step.
- To propose and evaluate modifications to the BDND algorithm.
- To improve image sharpness after impulse noise removal.
Main Methods:
- Proposed two modifications to the filtering step of the BDND algorithm.
- Conducted experimental evaluations to compare the modified BDND with the original algorithm.
- Assessed image quality based on sharpness and noise reduction effectiveness.
Main Results:
- The proposed modifications effectively addressed issues in the BDND filtering step.
- Experimental results demonstrated that the modified BDND algorithm produces sharper images.
- The enhanced filter maintained the noise removal capabilities of switching median filters.
Conclusions:
- The modifications significantly improve the performance of the BDND algorithm for impulse noise removal.
- The enhanced BDND filter offers a better trade-off between noise suppression and image detail preservation.
- This work contributes to the development of more effective image denoising techniques.
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