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Improved Adaptive Weighted Mean Filter for Salt-and-Pepper Noise Removal

Uğur Erkan, Dang N. H. Thanh, Serdar Enginoğlu, Samet Memiş

20202020 International Conference on Electrical, Communication, and Computer Engineering (ICECCE)32 citationsDOIOpen Access PDF

Abstract

In this study, we propose an improved adaptive weighted mean filter (IAWMF) to remove salt-and-pepper noise. The most prominent advantage of IAWMF is its ability to take into account the weights of noise-free pixels in the adaptive window. Hence, the new grey value occurs closer to the original grey value of the centre pixel than the grey value computed by the adaptive weighted mean filter (AWMF). Moreover, the proposed method utilises the advantage of AWMF to reduce the error of detecting noisy pixels. In the experiments, we compare the denoising results of the proposed method with other state-of-the-art image denoising methods. The results confirm that IAWMF outperforms other methods.

Topics & Concepts

Salt-and-pepper noisePixelNon-local meansNoise reductionMedian filterArtificial intelligenceComputer scienceNoise (video)Filter (signal processing)Adaptive filterBilateral filterImage denoisingPattern recognition (psychology)Computer visionMathematicsImage (mathematics)Image processingAlgorithmImage and Signal Denoising MethodsBlind Source Separation TechniquesAdvanced Image Fusion Techniques