Adaptive switching weighted median filter framework for suppressing salt-and-pepper noise

The paper presents an efficient approach for suppressing salt-and-pepper (S & P) noise under adaptive switching weighted median filter (ASWMF) framework. The ASWMF includes noise detection and noise removal stages. The proposed method first classifies a pixel into either “noise-free pixel” or “noise pixel” by checking noise candidate with the local mean value using noise detection stage. Then, the detected noisy pixels are replaced by their weighted median values using adaptive weighted median filter within a window size of 3×3 or 5×5. The proposed method is compared to several denoising schemes in terms of key performance indicators. Test results demonstrated superiority and efficiency over other methods in removing S & P noise up to percentage of 90%.