TDI遥感图像中畸变像移模糊的去除

采用离轴三反射结构的大视场空间相机存在较大的光学畸变，导致引入时间延迟积分(Time Delay Integration, TDI)技术的面阵探测器在推扫成像时产生像移模糊。根据畸变引起的TDI成像退化原理，将畸变像移模糊转化为非均匀运动模糊，通过求解像移路径计算初始模糊核，将其作为先验信息，建立半盲复原模型进一步细化模糊核。利用初始模糊核复原的粗略图像边缘指导模糊核的细化，提出一种多方向权重异性的全变差模型提取图像结构信息。为了增强先验信息对模糊核细化的约束，构建了含有初始模糊核的正则项，使模糊核的估计不过度依赖于图像内容，采用多尺度迭代方法求解。最后用正则化约束的非盲反卷积方法去除图像模糊。实验结果表明:与现有的几种去模糊算法相比，所提方法的去模糊效果不仅清晰自然且对不同样本图像的模糊核估计更稳定。

Removal of image motion blur caused by distortion in TDI remote-sensing image

The wide-field space camera with off-axis and three-reflection structure had large optical distortion, which led to the image motion blur during push-broom imaging of the plane-array detector with time delay integration (TDI) technology. According to the principle of TDI imaging degradation caused by distortion, the distortded image motion blur was converted into non-uniform motion blur, and the initial blur kernel was solved by fitting the image motion path, which was used as prior information to establish a semi-blind restoration model to further refine the blur kernel. Using the rough image edge restored by the initial blur kernel to guide the refinement, a multi-directional weight-heterogeneous total variation model was proposed to extract image structure information. In order to enhance the constraints of prior information on the refinement of the blur kernel, a regular term containing the initial blur kernel was constructed, so that the estimation of the blur kernel did not depend excessively on the image content, and a multi-scale iterative method was used to solve the problem. Finally, a regularization-constrained non-blind deconvolution method was used to remove image blur. Experimental results show that the compared with several existing deblurring algorithms, the deblurring effect of the proposed method is not only clear and natural, but also more stable in the estimation of the blur kernel of different sample images.