Fuzzy Logic Denoiser: An Approach for Salt and Pepper Noise Removal in Digital Images

Digital images often suffer from salt and pepper noise, adversely impacting image quality and subsequent processing tasks. This paper introduces an innovative method for salt and pepper noise removal employing fuzzy logic. The proposed approach first intelligently identify noisy pixels by considering both spatial and intensity information. Following the identification process, a fuzzy filtering strategy is applied to dynamically adjust pixel values based on the number of good pixels, ensuring effective noise reduction while preserving crucial image features. Comprehensive experiments on diverse image datasets, featuring varying noise levels, substantiate the superior performance of our fuzzy-based method in comparison to existing denoising techniques. The method not only outperforms in terms of quantitative metrics but also exhibits visually appealing results. Its adaptability is demonstrated across different scenarios, making it a robust solution for real-world applications where accurate image analysis hinges on noise-free data.