Coregistration Of Synthetic Aperture Radar Images Research Articles

Variational approach for rigid co-registration of optical/SAR satellite images in agricultural areas

In this paper the problem of Synthetic Aperture Radar (SAR) and optical satellite images co-registration is considered. Because of the distinct natures of SAR and optical images, there exist huge radiometric and geometric differences between such images. As a result, the traditional registration approaches are no longer applicable in this case and it makes the registration process challenging. Mostly motivated by the crop field monitoring problem, we propose a new variational approach to the co-registration of SAR and optical images. The core idea of our approach is to involve into consideration a constrained optimization problem on the set of affine transformations for which the cost functional is the Lp-cross-correlation between sustainable parts of two fattened skeletons for the selectively smoothed SAR image and the luma component of an optical image, respectively.We discuss the consistency of the proposed statement of this problem, propose the scheme for its regularization, derive the corresponding optimality system, and describe in detail the algorithm for the practical implementation of co-registration procedure. To evaluate the performance of the proposed approach, we illustrate its crucial steps with the help of several numerical experiments and real satellite images.

Multithreading Based Parallel Processing for Image Geometric Coregistration in SAR Interferometry

Within the framework of multi-temporal Synthetic Aperture Radar (SAR) interferometric processing, image coregistration is a fundamental operation that might be extremely time-consuming. This paper explores the possibility of addressing fast and accurate SAR image geometric coregistration, with sub-pixel accuracy and in the presence of a complex 3-D object scene, by exploiting the parallelism offered by shared-memory architectures. An efficient and scalable processor is proposed by designing a parallel algorithm incorporating thread-level parallelism for solving the inherent computationally intensive problem. The adopted functional scheme is first mathematically framed and then investigated in detail in terms of its computational structures. Subsequently, a parallel version of the algorithm is designed, according to a fork-join model, by suitably taking into account the granularity of the decomposition, load-balancing, and different scheduling strategies. The developed parallel algorithm implements parallelism at the thread-level by using OpenMP (Open Multi-Processing) and it is specifically targeted at shared-memory multiprocessors. The parallel performance of the implemented multithreading-based SAR image coregistration prototype processor is experimentally investigated and quantitatively assessed by processing high-resolution X-band COSMO-SkyMed SAR data and using two different multicore architectures. The effectiveness of the developed multithreaded prototype solution in fully benefitting from the computing power offered by multicore processors has successfully been demonstrated via a suitable experimental performance analysis conducted in terms of parallel speedup and efficiency. The demonstrated scalable performance and portability of the developed parallel processor confirm its potential for operational use in the interferometric SAR data processing at large scales.

Multi-sensor SAR image coregistration based on stable convex corner points and double matching network

ABSTRACTSince significant differences exist in imaging principle and parameters of different synthetic aperture radar (SAR) sensors, the detection of stable consistent features and accurate feature matching are difficult to implement in multi-sensor SAR image coregistration. To solve these problems, this study proposed a coregistration method based on stable convex corner point and double matching network. The stable convex corner points were detected from stable convex polygons, which were obtained by the proposed local stable extremal region extraction method, convex polygon fitting, and normalization. The double matching network was divided into coarse and fine matching. We utilized spatial relationships of the stable convex polygons to build a coarse matching network, and the fine matching network was formed by stable convex corner points. Precise matching was achieved with region features and spatial relations. Experimental results on multi-sensor SAR images showed that the proposed method had superior performance.

Nonrigid synthetic aperture radar and optical image coregistration by combining local rigid transformations using a Kohonen network.

This study proposes a new algorithm for nonrigid coregistration of synthetic aperture radar (SAR) and optical images. The proposed algorithm employs point features extracted by the binary robust invariant scalable keypoints algorithm and a new method called weighted bidirectional matching for initial correspondence. To refine false matches, we assume that the transformation between SAR and optical images is locally rigid. This property is used to refine false matches by assigning scores to matched pairs and clustering local rigid transformations using a two-layer Kohonen network. Finally, the thin plate spline algorithm and mutual information are used for nonrigid coregistration of SAR and optical images.

Hierarchical approach for synthetic aperture radar and optical image coregistration using local and global geometric relationship of invariant features

A hierarchical method is proposed for synthetic aperture radar (SAR) and optical image coregistration. We use local invariant salient points extracted by the binary robust invariant scalable keypoints (BRISK) algorithm for SAR and optical image coregistration. However, the matched points are highly erroneous because of the speckle noise in SAR images and the different structures of SAR and optical images. Therefore, an adaptive and elliptical bilateral filter is used to remove the speckle noise. Additionally, a hierarchical approach is used for coregistration using the local and global geometrical relationship of BRISK features. For each salient point in the optical image, three closest matched points are found in the SAR image. The geometrical relationship of the matched points is determined in the local areas around the salient and matched points, and matched pairs with fewer geometrical matching scores are removed. At the final stage of the algorithm, the projective global model between optical and SAR images is obtained using a robust statistic and the remaining false matches are refined. Experimental results and the comparison of the results of the proposed algorithm with those of the existing approaches show that the proposed algorithm is more efficient.

SAR image coregistration using fringe definition detection

In order to overcome the limitation of cross correlation coregistration method for Synthetic Aperture Radar (SAR) interferometric pairs with low coherence, a new image coregistration algorithm based on Fringe Definition Detection (FDD) is presented in this paper. The Fourier transformation was utilized to obtain spectrum characteristics of interferometric fringes. The ratio between spectrum mean and peak was proposed as the evaluation index for identifying homologous pixels from interferometric images. The satellites ERS-1/2 C-band SAR acquisitions covering the Yangtze River plain delta, eastern China and ALOS/PALSAR L-band images over the Longmen Shan mountainous area, southwestern China were respectively employed in the experiment to validate the proposed coregistration method. The testing results suggested that the derived Digital Elevation Model (DEM) from FDD method had good agreement with that from the cross correlation method as well as the reference DEM at high coherence area. However, The FDD method achieved a totally improved topographic mapping accuracy by 24 percent in comparison to the cross correlation method. The FDD method also showed better robustness and achieved relatively higher performance for SAR image coregistration in mountainous areas with low coherence.

Extraction of interest points by Harris interest operator for synthetic aperture radar image coregistration

In image coregistration of synthetic aperture radar (SAR) interferometry, a set of points is selected for tie point matching. Generally, some special points are possibly selected as tie points to improve the reliability of coregistration. However, special points cannot always be found in an image. Therefore points in grid form are commonly selected for image coregistration and this makes the results not as reliable as special points do. In this study, hence, a series of points detected by Harris interest operator (HIO) are used as tie points for SAR image coregistration. After wavelet decomposition of a SAR image, the basic energy is reserved in the low-pass subimage and this benefits the extraction of interest points conducted by HIO on the highest level. Three pairs of SAR image in Hong Kong area are used to prove the efficiency of the proposed method. For comparison, image coregistration based on grid points and interest points are implemented, respectively, in which different numbers of points are adopted. Based on the analysis of experimental results, it is found that the quality of interferogram is greatly improved by interest points and coregistration with interest points is more reliable.

Wavelet and Karhunen Loève transformations applied to SAR signals and images

We developed two new tools to deal with synthetic aperture radar (SAR) images, based on two different and powerful mathematical formalism: wavelets (WT) and Karhunen Loève transforms (KLT). WT are used to remove the undesirable speckle, which comes from the specific measurement process of SAR systems, and KLT for the co-registration of SAR images.

Coregistration of Multiangle Fine Spatial Resolution SAR Images

Provides a first assessment of a coregistration technique suitable for multiangle fine spatial resolution synthetic aperture radar (SAR) images. The technique is based on crossroad and road junction extraction and matching and exploits recently introduced road extraction routines for SAR data. These features are matched using relational and geometrical analysis. Results are encouraging and show the possibility to exploit multiangle SAR available from future airborne and satellite missions.

Minimising the tie patch window size for SAR image co-registration

Owing to the presence of relatively large amounts of noise, co-registration of synthetic aperture radar (SAR) images typically involves matching of local area baaed ‘tie patches’ rather than feature based ‘tie points’. Some applications require small tie patch windows, e.g. stereo SAR. Small tie patch windows, however, can lead to poor estimates of the local co-registration parameters. A procedure to minimise the tie patch window size while retaining ‘confidence’ in the local co-registration result is proposed. Background theory to the procedure and the results of an experimental study are presented.