Rigorous Co-Registration of KOMPSAT-3 Multispectral and Panchromatic Images for Pan-Sharpening Image Fusion.

KOMPSAT-3, a Korean earth observing satellite, provides the panchromatic (PAN) band and four multispectral (MS) bands. They can be fused to obtain a pan-sharpened image of higher resolution in both the spectral and spatial domain, which is more informative and interpretative for visual inspection. In KOMPSAT-3 Advanced Earth Imaging Sensor System (AEISS) uni-focal camera system, the precise sensor alignment is a prerequisite for the fusion of MS and PAN images because MS and PAN Charge-Coupled Device (CCD) sensors are installed with certain offsets. In addition, exterior effects associated with the ephemeris and terrain elevation lead to the geometric discrepancy between MS and PAN images. Therefore, we propose a rigorous co-registration of KOMPSAT-3 MS and PAN images based on physical sensor modeling. We evaluated the impacts of CCD line offsets, ephemeris, and terrain elevation on the difference in image coordinates. The analysis enables precise co-registration modeling between MS and PAN images. An experiment with KOMPSAT-3 images produced negligible geometric discrepancy between MS and PAN images.

Automated Geo/Co-Registration of Multi-Temporal Very-High-Resolution Imagery.

For time-series analysis using very-high-resolution (VHR) multi-temporal satellite images, both accurate georegistration to the map coordinates and subpixel-level co-registration among the images should be conducted. However, applying well-known matching methods, such as scale-invariant feature transform and speeded up robust features for VHR multi-temporal images, has limitations. First, they cannot be used for matching an optical image to heterogeneous non-optical data for georegistration. Second, they produce a local misalignment induced by differences in acquisition conditions, such as acquisition platform stability, the sensor's off-nadir angle, and relief displacement of the considered scene. Therefore, this study addresses the problem by proposing an automated geo/co-registration framework for full-scene multi-temporal images acquired from a VHR optical satellite sensor. The proposed method comprises two primary steps: (1) a global georegistration process, followed by (2) a fine co-registration process. During the first step, two-dimensional multi-temporal satellite images are matched to three-dimensional topographic maps to assign the map coordinates. During the second step, a local analysis of registration noise pixels extracted between the multi-temporal images that have been mapped to the map coordinates is conducted to extract a large number of well-distributed corresponding points (CPs). The CPs are finally used to construct a non-rigid transformation function that enables minimization of the local misalignment existing among the images. Experiments conducted on five Kompsat-3 full scenes confirmed the effectiveness of the proposed framework, showing that the georegistration performance resulted in an approximately pixel-level accuracy for most of the scenes, and the co-registration performance further improved the results among all combinations of the georegistered Kompsat-3 image pairs by increasing the calculated cross-correlation values.

3D Power Line Extraction from Multiple Aerial Images.

Power lines are cables that carry electrical power from a power plant to an electrical substation. They must be connected between the tower structures in such a way that ensures minimum tension and sufficient clearance from the ground. Power lines can stretch and sag with the changing weather, eventually exceeding the planned tolerances. The excessive sags can then cause serious accidents, while hindering the durability of the power lines. We used photogrammetric techniques with a low-cost drone to achieve efficient 3D mapping of power lines that are often difficult to approach. Unlike the conventional image-to-object space approach, we used the object-to-image space approach using cubic grid points. We processed four strips of aerial images to automatically extract the power line points in the object space. Experimental results showed that the approach could successfully extract the positions of the power line points for power line generation and sag measurement with the elevation accuracy of a few centimeters.

Geometric Calibration and Validation of Kompsat-3A AEISS-A Camera.

Kompsat-3A, which was launched on 25 March 2015, is a sister spacecraft of the Kompsat-3 developed by the Korea Aerospace Research Institute (KARI). Kompsat-3A's AEISS-A (Advanced Electronic Image Scanning System-A) camera is similar to Kompsat-3's AEISS but it was designed to provide PAN (Panchromatic) resolution of 0.55 m, MS (multispectral) resolution of 2.20 m, and TIR (thermal infrared) at 5.5 m resolution. In this paper we present the geometric calibration and validation work of Kompsat-3A that was completed last year. A set of images over the test sites was taken for two months and was utilized for the work. The workflow includes the boresight calibration, CCDs (charge-coupled devices) alignment and focal length determination, the merge of two CCD lines, and the band-to-band registration. Then, the positional accuracies without any GCPs (ground control points) were validated for hundreds of test sites across the world using various image acquisition modes. In addition, we checked the planimetric accuracy by bundle adjustments with GCPs.