Salt-and-Pepper Noise Suppression Using Adaptive Noise-Adaptive Fuzzy Selection Filter
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This paper presents a salt-and-pepper noise suppression method based on an adaptive noise-aware fuzzy selection filter. The proposed approach effectively reduces salt-and-pepper noise in images while preserving important detail information. The implementation begins with pixel-value analysis to identify noise-corrupted pixels using threshold-based detection algorithms. The core algorithm employs an adaptive fuzzy selection filter that dynamically adjusts blurring intensity based on quantified noise levels through fuzzy logic rules. Key functions include noise density estimation and membership function optimization for intelligent filtering decisions. Finally, processed images are compared with originals using quantitative metrics like PSNR and SSIM for performance evaluation. Experimental results demonstrate that this method achieves effective noise suppression while maintaining image clarity and structural details.
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