In order to improve the visual effect of image denoising

according to natural images often contain more repetitive structure and bilateral filter have advantages in image denoising

present a new image denoising algorithm based on bilateral filtering and non-local means（ NLM）. This method uses idea of NLM to estimate current pixel gray value. In image denoising process

not only impacts of current pixel gray value on result of prediction is taken into account

but also considered position relationship between current pixel and surrounding pixel. Build position coefficients in non-local neighborhood to constraint forecast results

considering homogeneity pixels similarity within the nonlocal neighborhood

design bilateral nonlocal mean filter. Experimental results show that running time of the algorithm is 0. 114 faster than bilateral filtering algorithm

peak signal-to-noise ratio（ PSNR） is improved for 0. 9

image similarity（ MSSIM） is increased for 0. 181

the image fidelity（ VIF） is increased for 0. 2147. The proposed method can better maintain integrity of image information; improve image brightness and clarity of image texture.