Abstract: In order to eliminate noise and preserve details in image, an algorithm of image denoising based on visual receptive fields properties is proposed. Based on neuron electrophysiology research result, an image denoising processing has been realized by simulating adaptive mechanism in primary visual cortex and response characteristics of visual receptive fields. First, noise is detected by a small scale template. Then, according to the size and the location of the noise, an ON/OFF receptive field model is applied to adaptively deal with the noise. Finally, the brightness of the image is adjusted. Compared with some current denoising methods, experimental results show that textures and edges information in images processed by this proposed algorithm are better preserved. It is superior to other methods in objective image quality indexes, such as peak signal to noise ratio (PSNR) and mean squared error (MSE). It can not only remove noise in image process, but has ability to strengthen image edge details as well.