In order to remove saltandpepper noise, a novel fuzzy switching adaptive weighted mean filter is proposed to eliminate the noise effectively. The method includes two stages: noise detection and noise elimination. In the first stage, first pixels are differentiated into two kinds: noiseless pixels and possible noise pixels. For the second kind pixels, we use the method of the sum of absolute luminance difference with processed pixels next to it and introduce two thresholds to divide them into three categories, noiseless pixels, lightly corrupted pixels and heavily corrupted pixels. In the second stage, a D8 distance relevant fuzzy switching adaptive weighted mean filter is proposed to remove saltandpepper noise. The simulation results show that compared with some existing methods, our method can effectively eliminate saltandpepper noise, the results contain more details, and have higher values of two typical image quality metrics: peak signaltonoise ratio (PSNR) and structural similarity (SSIM). Our method saves over 65% processing time compared with the adaptive weighted mean filter, which has the most similar results.