The work aims to study the adaptive color noise image denoising method based on bilateral filtering for the purpose of overcoming the feature blurring in color image after denoising. The color noise image was decomposed into approximate component, horizontal detail component, vertical detail component and diagonal detail component by the two-dimensional discrete wavelet transform (DWT). According to the normalized variance ratio of components of DWT in each direction, the RBF neural network was used to construct the bilateral filter coefficient model to determine the best denoising coefficient in different directions, propose an adaptive denoising method for color noise image (DWT-ABF), and compare this method with the conventional method. In the different types of noises and mixed noise distortion, the proposed method could effectively remove the noise and preserve the detail information of the image. Compared with other methods, the images denoised based on DWT-ABF had higher PSNR value. The DWT-ABF overcomes the defect that traditional bilateral filtering is unable to determine the optimal parameter, and it also well solves the feature blurring of denoised image.