An automatic co-registration approach for optical and SAR data in urban areas

Abstract

With the increasing applications of multisource remote sensing, the synergistic use of optical and Synthetic Aperture Radar (SAR) remote sensing images is becoming increasingly popular. Although numerous approaches have been proposed to register satellite images between two optical images or between two SAR images, these approaches cannot be directly applied to register optical and SAR images due to the differences of imaging mechanism between optical and SAR remote sensing. Therefore, the co-registration between optical and SAR images remains challenging, especially in urban areas where surface geometric configuration is much more complex. This study aims to propose a fast and automatic approach for optical and SAR data co-registration based on an assumption of affine transformation between the two images. With a set of initial homologous points generated automatically, an optimization is applied towards the initial homologous points on the SAR images subject to an affine transformation model and a given threshold of root mean square errors (RMSEs) for the co-registration. Three various data sets of optical and SAR images, including SPOT-5 and ENVISAT ASAR, Landsat TM and ENVISAT ASAR, and SPOT-5 and ALOS PALSAR, were employed to test and validate the effectiveness of the proposed method. Experimental results demonstrate the promising effectiveness of the proposed approach with a significant reduction of RMSE compared with the initial homologous points. The proposed approach is especially applicable in urban areas where the uncertain errors of homologous points in SAR images are higher due to the speckles and foreshortening, layover and shadows from tall buildings.

Geometrical Matching of SAR and Optical Images Utilizing ASIFT Features for SAR-based Navigation Aided Systems

“…The experiments proved that the proposed method for the geometrical matching of SAR and optical images utilizing ASIFT features for SAR-based Navigation Aided Systems is suitable for compute the corrections to the SAR images' direct georeferencing. In the literature, there are many methods and algorithms for this type of data co-registration [9,[11][12][13]15,16,18,19]. All of these algorithms were tested on SAR images and optical images acquired from space.…”

“…The process of image registration refers to the alignment of two or more images of the same scene which might be obtained with the same sensor, time, and imaging conditions, as well as by different sensors and viewpoints. The process of orientating optical and SAR images is still an open issue, which creates many challenges [9][10][11][12][13][14][15][16][17][18][19]. Many issues can be dealt with in the process of the synergy of optical and SAR data, due to the great differences between passive and active remote sensing techniques.…”

“…Many issues can be dealt with in the process of the synergy of optical and SAR data, due to the great differences between passive and active remote sensing techniques. One of the issues is the problem with the speckle noise that influences the detection of robust corresponding/tie points [9,[11][12][13]15,16,18,19]. Another issue is related to the differences in the image geometry acquired from these two devices [9,[11][12][13]15,16,18,19].…”

“…One of the issues is the problem with the speckle noise that influences the detection of robust corresponding/tie points [9,[11][12][13]15,16,18,19]. Another issue is related to the differences in the image geometry acquired from these two devices [9,[11][12][13]15,16,18,19]. Thus, many co-registration approaches have been proposed (e.g., [9][10][11][12][13][14][15][16][17][18][19]), but, in general, these approaches might be divided into two main categories: area-and feature-based methods.…”

“…Another issue is related to the differences in the image geometry acquired from these two devices [9,[11][12][13]15,16,18,19]. Thus, many co-registration approaches have been proposed (e.g., [9][10][11][12][13][14][15][16][17][18][19]), but, in general, these approaches might be divided into two main categories: area-and feature-based methods. Nowadays, the Structure from Motion (SfM) methods, which are mostly based on the feature-based approach, are used for the co-registration of spaceborne SAR and optical images [9,[11][12][13]15,16,18,19].…”