Abstract: After analyzing remote sensing image structure and its main difference from noise signals, this paper utilizes directional information in image signal and proposes a translation invariant omnidirectional lifting (TI-OL) for remote sensing image noise removal. By integrating cycle spinning, Gabor wavelet filter and image rotate skills into traditional adaptive directional lifting (ADL), the proposed algorithm overcomes three drawbacks in ADL as lacking of translation invariance, inefficiency in local direction estimation and limited transform direction distribution. In this way, the proposed method can reduce Gibbs effects in the denoising result, promote the accuracy of orientation estimation and guarantee an optimal representation for textural information. Experimental results demonstrate that the proposed method can effectively remove noise while protecting the image detail information. It outperforms state-of-art denoising algorithm in terms of both objective (PSNR) and subjective (SSIM) evaluation.