Influence of camera distortions on satellite image registration and change detection applications

Ayoub, F.; Leprince, S.; Binet, Renaud; Lewis, K. W.; Aharonson, O.; Avouac, Jean Philippe

doi:10.1109/igarss.2008.4779184

Cited by 45 publications

(38 citation statements)

References 10 publications

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“…Other kinds of references can also be used: spatial high resolution images can be used instead of aerial images [2], [4]. The ground sampling distance ratio between the reference and the images must be sufficiently low, in order to consider the reference as perfect [6], [7]. The most difficult is to have a 3d reference which can be produced with stereoscopic spatial data.…”

Section: Classical Methods Using a Geometric Supersitementioning

confidence: 99%

Attitude Assessment Using Pleiades-Hr Capabilities

Delevit

Greslou

Amberg

et al. 2012

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Since SPOT1, the French national space centre (CNES) has worked on improving the geometry of Earth observation spacecrafts. The accuracy of sensor calibration is one of the main key points for any Earth observation application such as orthorectification, DEM generation or surface change detection. For the last twenty years CNES has developed two families of methods: absolute methods and relative methods. These methods are used to characterize a pushbroom acquisition along the detector line and the time line. By this way, the viewing directions are measured and the residual of the spacecraft's attitude angles (not restituted by the Attitude and Orbit Control System) is estimated. This information can complete the geometric model of all the scenes acquired by the instrument and is used in all geometric applications. This paper presents new attitude assessment methods taking advantage of the capabilities of Pléiades-HR in terms of agility and focal plane arrangement -panchromatic band and multispectral (MS) bands.

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Section: Classical Methods Using a Geometric Supersitementioning

confidence: 99%

Attitude Assessment Using Pleiades-Hr Capabilities

Delevit

Greslou

Amberg

et al. 2012

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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show abstract

“…Theoretically, the geographical coordinates of the corrected images from different sensors should be extremely close, and the images can be fused directly. However, the positioning accuracy of different images is influenced by the limited manufacturing technology of the charge-coupled device, focal plane distortion, and unrecorded spacecraft jitter [36]. In our actual data processing, the geometrically corrected images of ZY-1-02C still exhibit a significant accuracy difference, which indicates that the image registration process should be conducted before image fusion.…”

Section: Introductionmentioning

confidence: 99%

Automatic Registration Method for Fusion of ZY-1-02C Satellite Images

Chen

Wang

et al. 2013

Remote Sensing

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Automatic image registration (AIR) has been widely studied in the fields of medical imaging, computer vision, and remote sensing. In various cases, such as image fusion, high registration accuracy should be achieved to meet application requirements. For satellite images, the large image size and unstable positioning accuracy resulting from the limited manufacturing technology of charge-coupled device, focal plane distortion, and unrecorded spacecraft jitter lead to difficulty in obtaining agreeable corresponding points for registration using only area-based matching or feature-based matching. In this situation, a coarse-to-fine matching strategy integrating two types of algorithms is proven feasible and effective. In this paper, an AIR method for application to the fusion of ZY-1-02C satellite imagery is proposed. First, the images are geometrically corrected. Coarse matching, based on scale invariant feature transform, is performed for the subsampled corrected images, and a rough global estimation is made with the matching results. Harris feature points are then extracted, and the coordinates of the corresponding points are calculated according to the global estimation results. Precise matching is conducted, based on normalized cross correlation and least squares matching. As complex image distortion cannot be precisely estimated, a local estimation using the structure of triangulated irregular network is applied to eliminate the false matches. Finally, image resampling is conducted, based on local affine transformation, to achieve high-precision registration. Experiments with ZY-1-02C datasets demonstrate that the accuracy of the proposed method meets the requirements of fusion application, and its efficiency is also suitable for the commercial operation of the automatic satellite data process system. OPEN ACCESSRemote Sens. 2014, 6 158

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“…Kirk and Mattson identified the problem of jitter of HiRISE and LRO through unexpected ripples on DTM products [13,14]. Ayoub et al detected the attitude jitter of ASTER, QuickBird and HiRISE satellites by analyzing undulating pattern on parallax maps obtained from dense matching of two orthoimages, and thus eliminated these artifacts on orthoimages [19]. Nuth and Kääb proposed a co-registration method for elevation data and found jitter of ASTER through significant biases in DEM after 3D co-registration [20].…”

Section: Introductionmentioning

confidence: 99%

“…However, those methods that depend on accurate GCPs or high-performance attitude sensors are economically and technically infeasible for many on-orbit satellites. For such reasons, a number of studies have been carried out to detect and analyze attitude jitter based on imagery, provided attitude data, RPCs and products such as digital elevation model (DEM) and orthoimages [3,[13][14][15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Framework of Jitter Detection and Compensation for High Resolution Satellites

Tong

et al. 2014

Remote Sensing

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Attitude jitter is a common phenomenon in the application of high resolution satellites, which may result in large errors of geo-positioning and mapping accuracy. Therefore, it is critical to detect and compensate attitude jitter to explore the full geometric potential of high resolution satellites. In this paper, a framework of jitter detection and compensation for high resolution satellites is proposed and some preliminary investigation is performed. Three methods for jitter detection are presented as follows. (1) The first one is based on multispectral images using parallax between two different bands in the image; (2) The second is based on stereo images using rational polynomial coefficients (RPCs); (3) The third is based on panchromatic images employing orthorectification processing. Based on the calculated parallax maps, the frequency and amplitude of the detected jitter are obtained. Subsequently, two approaches for jitter compensation are conducted. (1) The first one is to conduct the compensation on image, which uses the derived parallax observations for resampling; (2) The second is to conduct the compensation on attitude data, which treats the influence of jitter on attitude as correction of charge-coupled device (CCD) viewing angles. Experiments with images from several satellites, such as ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiaometer), LRO (Lunar Reconnaissance 3945Orbiter) and ZY-3 (ZiYuan-3) demonstrate the promising performance and feasibility of the proposed framework.

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Influence of camera distortions on satellite image registration and change detection applications

Cited by 45 publications

References 10 publications

Attitude Assessment Using Pleiades-Hr Capabilities

Attitude Assessment Using Pleiades-Hr Capabilities

Automatic Registration Method for Fusion of ZY-1-02C Satellite Images

Framework of Jitter Detection and Compensation for High Resolution Satellites

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