Abstract
Automatic image registration of optical-to-Synthetic aperture radar (SAR) images is difficult because of the inconsistency of radiometric and geometric properties between the optical image and the SAR image. The intensity-based methods may require many calculations and be ineffective when there are geometric distortions between these two images. The feature-based methods have high requirements on features, and there are certain challenges in feature extraction and matching. A new automatic optical-to-SAR image registration framework is proposed in this paper. First, modified holistically nested edge detection is employed to detect the main contours in both the optical and SAR images. Second, a mesh grid strategy is presented to perform a coarse-to-fine registration. The coarse registration calculates the feature matching and summarizes the preliminary results for the fine registration process. Finally, moving direct linear transformation is introduced to perform a homography warp to alleviate parallax. The experimental results show the effectiveness and accuracy of our proposed method.
Highlights
IntroductionImage registration is the process of matching and overlaying two images obtained at different times, from different sensors or under different conditions, such as the weather, illumination, camera position and angle [1]
For these three image pairs, PPCM completes the registration of all the datasets and has the minimum error, it is more robust than other comparison methods
The mesh grid strategy provides the templates required for FDCM and evaluates the fast directional chamfer matching results to obtain a coarse matching result
Summary
Image registration is the process of matching and overlaying two images obtained at different times, from different sensors or under different conditions, such as the weather, illumination, camera position and angle [1]. Image registration has been widely used in remote sensing data analysis, computer vision, image processing and other fields. Synthetic aperture radar (SAR) can obtain images at any time of the day and night independently of the weather conditions. SAR has a larger detection range than that for collecting optical images and can find targets that are not discovered by optical sensors. The registration of optical images and SAR images uses the advantages of both data types to obtain complementary information, which makes it easier to detect and identify the object of the image and has greater accuracy [3]
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