Lijun Lu

A Uniform SIFT-Like Algorithm for SAR Image Registration

In this letter, a uniform scale-invariant feature transform (SIFT)-like algorithm is proposed for synthetic aperture radar (SAR) image registration, which can extract enough robust, reliable, and uniformly distributed features by the strategies of optimal feature selection based on a Voronoi diagram and feature scale-space proportional extraction. SAR images, taken from different viewpoints by an airborne sensor and at different times by spaceborne sensors, were used as test data to validate the effectiveness of the proposed algorithm. The indexes of local density and global coverage were used to assess the spatial distribution of matches. Compared with the traditional SIFT-like algorithm for SAR images (SAR-SIFT), the results show that the proposed algorithm can increase the number of matches and optimize their spatial distribution.

Woodland Extraction from High-Resolution CASMSAR Data Based on Dempster-Shafer Evidence Theory Fusion

Mapping and monitoring of woodland resources is necessary, since woodland is vital for the natural environment and human survival. The intent of this paper is to propose a fusion scheme for woodland extraction with different frequency (P- and X-band) polarimetric synthetic aperture radar (PolSAR) and interferometric SAR (InSAR) data. In the study area of Hanjietou, China, a supervised complex Wishart classifier based on the initial polarimetric feature analysis was first applied to the PolSAR data and achieved an overall accuracy of 88%. An unsupervised classification based on elevation threshold segmentation was then applied to the InSAR data, with an overall accuracy of 90%. After Dempster-Shafer (D-S) evidence theory fusion processing for the PolSAR and InSAR classification results, the overall accuracy of fusion result reached 95%. It was found the proposed fusion method facilitates the reduction of polarimetric and interferometric SAR classification errors, and is suitable for the extraction of large areas of land cover with a uniform texture and height. The woodland extraction accuracy of the study area was sufficiently high (producer’s accuracy of 96% and user’s accuracy of 96%) enough that the woodland map generated from the fusion result can meet the demands of forest resource mapping and monitoring.

Land cover classification and height extraction experiments using Chinese airborne X-band PolInSAR system in China

In this paper, we describe our land cover classification and height extraction experiments with high-resolution X-band polarimetric interferometric synthetic aperture radar (PolInSAR) data acquired by Chinese airborne PolInSAR system over Linshui in southern China. The experimental area contains plenty of natural and artificial objects. We present two polarimetric synthetic aperture radar (PolSAR) classification schemes for different land cover types. An Oriented-Object classification scheme based on hierarchical segmentation is employed to the regular land cover classification experiment. The Entropy–PSD unsupervised classification method based on pixel is employed to the low backscattering targets classification experiment. Fully taking advantage of the characteristics of the multi-baseline data set, a dual-baseline polarimetric interferometry method is applied to the PolInSAR experiment of height extraction. Our PolSAR and PolInSAR experiment results demonstrate that high-resolution X-band PolInSAR imagery acquired by Chinese airborne SAR system have great application potential for land classification and height extraction.

Multi-mode PolInSAR experiments using an airborne X-band SAR system in China

In this paper, we describe our polarimetric interferometric synthetic aperture radar (PolInSAR) experiments with high-resolution X-band data acquired by a multi-mode airborne SAR system over an area of Linshui in southern China. First, we introduce our latest multi-mode X-band airborne imaging radar system (Multi-Mode-XSAR), which integrates three operation modes of bistatic, ping-pong, and mixed. Then, the Multi-Mode-XSAR data set and the corresponding ground measurements in test areas are briefly described. Considering the characteristics of the Multi-Mode-XSAR imagery, a dual-baseline polarimetric interferometry (DPI) method is proposed in this article. The proposed method guarantees a high coherence on the full polarimetric data and combines the benefits of short and long baselines to facilitate the phase unwrapping and promote height sensitivity. Our PolInSAR experiment results demonstrate that the DPI method is capable of generating DSM with higher accuracy than other multi-baseline (MB) methods and the Multi-Mode-XSAR imagery has great potential in PolInSAR applications.

Man-made objects detection using multi-mode X-band PolInSAR data

This paper makes man-made objects detection experiment with the high-resolution X-band PolInSAR data acquired by Multi-mode airborne SAR system over an area around Linshui. Polarimetric and PolInSAR analysis for manmade objects are presented, some polarimetric and PolInSAR descriptors sensitive to man-made objects are selected. Experimental result of man-made objects detection demonstrates that multi-mode-XSAR dataset have intuitive capabilities for application of man-made objects detection.

CASMSAR: the first Chinese airborne SAR mapping system

In this paper, we present an overall description of the newest Chinese airborne SAR mapping system CASMSAR, which is developed by a group led by Chinese Academy of Surveying and Mapping (CASM). Since CASMSAR is equipped with two independent high-resolution SAR sensors (X-band and P-band), it allows the integration of interferometric and fully polarimetric functions. Another novel feature of CASMSAR is the software control of system monitoring and flight navigation display, which makes the whole system very intelligent and operational. The data processing software systems of CASMSAR consists of five subsystems. CASMSAR works in several modes. The most important two of them are used for mapping in scale of 1:10,000 and 1:50,000. Initial data were acquired during several testing flight campaigns in last year, and experimental results have proved that the system works well and the performance is better than expectation.

A Study on Extraction of Man-Made Targets Using SVM Method from High Resolution PolInSAR Data

This paper studys a man-made target extraction technique using SVM (Support Vector Machine) method from high resolution PolInSAR(polarimetric Interferometric synthetic aperture radar ) data. Fully polarimetric interferometric data in X band was acquired by a China-made airborne SAR system in January 2010, over the Linshui area in Hainan province. This study focuses on man-made targets extraction in Linshui area, where the ground survey allows the validation of the final extraction results. Different PolSAR (polarimetric SAR) and PolInSAR(polarimetric interferometric SAR) feature indicators, such as H/A/α,based on the Pauli formalism or an optimal set of coherences are subsequently analyzed and the representatives of features are selected. In order to consider effect of man-made targets extraction with different feature indicators, the SVM method is investigated. The results based on PolSAR, PolInSAR and combined PolSAR and PolInSAR features are respectively compared, the best result is obtained via combining PolSAR and PolInSAR features.