Due to severe speckle noise in synthetic aperture radar (SAR) images and the large nonlinear intensity differences between SAR and optical images, the registration of SAR and optical images is a challenging problem that remains to be solved. In this paper, an improved nonlinear scale-invariant feature transform (SIFT)-framework-based algorithm that combines spatial feature detection with local frequency-domain description for the registration of SAR and optical images is proposed. First, multiscale representations of the SAR and optical images are constructed based on nonlinear diffusion to better preserve edges and obtain consistent edge information. The ratio of exponentially weighted averages (ROEWA) operator and the Sobel operator are utilized in the process of scale space construction to calculate consistent gradient information. Then, a new feature detection strategy based on the Harris–Laplace ROEWA and Harris–Laplace Sobel techniques is proposed to detect stable and repeatable keypoints in the scale space. Finally, a novel descriptor, called the rotation-invariant amplitudes of log-Gabor orientation histograms (RI-ALGH), and a simplified version, ALGH, are proposed. The proposed descriptors are built based on the amplitudes of multiscale and multiorientation log-Gabor responses and utilize an improved spatial structure of the gradient location and orientation histogram (GLOH) descriptor, which is robust to local distortions. The experimental results on both simulated and real images demonstrate that the proposed method can achieve better results than other state-of-the-art methods in terms of registration accuracy.

由于合成孔径雷达（SAR）图像中存在严重的斑点噪声，并且SAR和光学图像之间存在较大的非线性强度差异，因此SAR和光学图像的配准是一个有待解决的难题。本文提出了一种改进的基于非线性尺度不变特征变换（SIFT）框架的算法，该算法将空间特征检测与局部频域描述相结合，用于SAR和光学图像的配准。首先，基于非线性扩散构造SAR和光学图像的多尺度表示，以更好地保留边缘并获得一致的边缘信息。在比例空间构建过程中，使用指数加权平均值之比（ROEWA）运算符和Sobel运算符来计算一致的梯度信息。然后，提出了一种基于Harris–Laplace ROEWA和Harris–Laplace Sobel技术的新特征检测策略，以检测尺度空间中的稳定和可重复的关键点。最后，提出了一种新颖的描述符，称为log-Gabor方向直方图的旋转不变幅度（RI-ALGH），以及一种简化的描述符ALGH。提出的描述符是基于多尺度和多方向对数Gabor响应的幅度构建的，并利用了改进的梯度位置和方向直方图（GLOH）描述符的空间结构，该结构对局部失真具有鲁棒性。在模拟图像和真实图像上的实验结果表明，该方法在配准精度方面比其他最新方法可以获得更好的结果。