In order to solve the problem that most of existing image denoising methods insufficiency preserve the details and enhance edges while implementing denoising, a new method for remote sensing image denoising is proposed, based on a combination of cycle spinning contourlet transform (CT), and the total variation (TV) minimization scheme. The proposed method relies on principles that CT scheme is well suited for preserving detailed and fine textures information of original image while TV minimization denoising scheme is capable of enhancing sharpened significant edges while denoising, therefore to fuse the two schemes using the proposed fusion rule can achieve better results. Compared with several commonly used approaches, the experimental results show that this novel algorithm is capable of reducing Gibbs phenomenon and staircase effect produced by CT and TV denoising methods respectively, superior both in visual quality of denoising and Peak Signal to Noise Ratio (PSNR), and preserves more spectral information and less spectral distortion simultaneously.