###### Abstract  
Synthetic aperture radar (SAR) satellites have an active sensor on board, which emits electromagnetic signals and measures the strength and time delay of the returned signal backscattered from ground objects. Optical images have rich spectral information, but it is easily affected by atmospheric attenuation and weather conditions. Thus, the study of the registration between these two images is of great significance. We present a novel method for SAR and optical image registration. In the stage of feature points extraction, the method combines phase consistency intensity screening and scale space grid division to obtain stable and uniform feature points from the image. During the stage of feature description, the method employs the extended phase consistency method to calculate the gradient amplitude and direction of the image, and improves the correctness of the main direction calculation and descriptor construction. Experimental results demonstrate its superior matching performance with respect to the state-of-the-art methods.  
remote sensing; image registration; SAR; SIFT 2023 13 1238 13 1238 13 1  
present, due to the great difference in imaging mechanism between SAR and optical images, the geometric and radiation characteristics of the images are different. In addition, the multiplicative speckle noise inherent in the SAR image brings many difficulties to the registration of SAR and optical images. Therefore, it is of great significance to study the registration of SAR and optical images.  
The SIFT algorithm [12] is a classic local invariant feature extraction method. The algorithm mainly detects extreme points in the Gaussian difference scale space as stable feature points, and at the same time it calculates the gradient direction histogram in the neighborhood of the image to construct the feature vector. In terms of its similar algorithms, the extraction of robust feature points and the calculation of basic gradient features are of great significance to the performance of this method. As mentioned above, due to the different imaging mechanisms and acquisition methods of optical and SAR images, there is a large non-linear radiation difference between these two kinds of images [13]. At the same time, there is an inherent multiplicative noise in SAR images, which will cause different extractions. The source image has a small number of feature points with the same name and poor robustness [14]. In addition, the main direction of the calculated feature points and the constructed descriptor are unreliable due to gradient calculation errors, which leads to a lower correct matching rate in the feature point matching stage.  
To solve the problems mentioned above, this paper conducts research from the two aspects of obtaining robust feature points with the same name and calculating the consistency gradient of heterogeneous images, and proposes a SIFT registration method based on uniform extraction of feature points and gradient consistency. In the stage of feature points extraction, the method combines phase consistency intensity screening and scale space grid division to obtain stable and uniform feature points from the image. In the feature description stage, the method employs the extended phase consistency method to calculate the gradient amplitude and direction of the image, and improves the correctness of the main direction calculation and descriptor construction compared with the original SIFT algorithm.