卫星搭载的有效载荷在进行在轨对地观测过程中，受仪器本身特性和地球固有特性因素的影响，在图像上会产生多种观测失准和干扰现象。如图像旋转现象，蝴蝶结效应以及探元非均匀性条纹现象等。针对这类可以预见到的冗余和条纹，对仪器设计优化以及借助卫星星历轨道等辅助数据和成熟的图像处理算法可以对其实现有效地恢复。仪器在轨运行期间新引入的周期性或非周期性干扰，则需综合运用多种数据来源和关于干扰产生原理的先验知识，并结合图像处理手段实现图像恢复，同时保存原有辐射信息的真实性，为定量研究提供高质量可靠的数据准备。本研究针对某卫星中波红外图像干扰条纹，利用星上定标数据，并通过条纹现象分析和产生机理分析，探索了一种新的基于空域信号补偿原理的图像干扰条纹处理算法，通过大量图像数据处理实践证明，该算法对图像质量改善明显，且在动态范围和辐射信息保存方面优于传统频域滤波算法。

An image obtained by a satellite in orbit may reflect a variety of inaccurate observations and different forms of interference, such as image rotation, the bow effect, and non-uniform stripes phenomena. These are attributed to the inherent characteristics of the Earth. These types of redundancy and stripes can be foreknown, and the image can be restored using design optimization, the satellite orbit ephemeris and image processing methods. The restoration of a periodic or aperiodic interference newly introduced in orbit requires the integrated use of multiple data sources, prior knowledge on the principle of interference, and appropriate image processing methods. Meanwhile, the authenticity of the original radiation information should be preserved for follow-up quantitative studies. In the present study, a new destriping method was introduced for processing of Mid-Infrared images. Using on-board calibration data and analysis of the stripes phenomenon and mechanism, a new spatial domain compensation algorithm was explored for the removal of image interference stripes. Results show that the image quality can be substantially improved by the proposed method. When compared with the frequency domain filtering algorithm, it is better in terms of both the dynamic range index and radiation information preservation.