Abstract: In order to overcome the inefficiency of existing filters in impulse noise removal, and achieve higher robustness and better effectiveness than the existing filters, an image denoising scheme based on trimmed mean and Gaussian weighted median is proposed. By exploiting the features of impulse noise and noise free pixels in distribution and intensity, the noisy pixels are first discriminated from noise free ones in a local statistical way, the pixels with minimum or maximum intensity and with less correlation with neighboring pixels, are taken as noisy pixels. And then, the noises in smooth region and detail region, are processed respectively by adaptive trimmed mean filter and adaptive Gaussian weighted median filter, the impact and correlation of neighboring pixels are presented by Gaussian weighted operator. Experimental results show that in terms of visual quality, PSNR and SSIM, and computational efficiency, the proposed method is superior to existing filters, preserves better the edges and detail structures of image while removes the noise thoroughly.