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 lack of translation invariance, inefficiency in local direction estimation and limitation on transform direction distribution. In this way, the proposed method can reduce Gibbs effects in thedenoising 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 algorithms in terms of both objective （PSNR） and subjective （SSIM） evaluation.%在分析遥感图像结构特征及其与噪声之间主要区别的基础上，利用图像信号的方向信息，提出基于移不变全方向角提升小波（TI—OL）抑制遥感图像噪声的方法。该方法在方向提升小波变换的基础上并利用循环平移，Gabor小波滤波器和图像旋转技术改进了方向提升小波在图像去噪过程中存在的三个弊端：缺乏移不变性质，图像局部方向信息判方法断缺乏噪声鲁棒性和变换方向分布有限。消除去噪结果中的吉布斯效应，提高图像方向信息判断的准确性并保证图像纹理方向始终落在方向提升能最优表示的方向区间内。试验结果证明所提方法在处理遥感图像的过程中能在去噪的同时保留图像的细节和边缘信息，对遥感图像中的边缘信息如道路和桥梁有较好的刻画性能，较传统方法去噪性能（PSNR）和主观视觉效果（SSIM）均有较大提高。
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