Bias-compensated RPCs for Sensor Orientation of High-resolution Satellite Imagery

Fraser, Clive S.; Hanley, Harry B.

doi:10.14358/pers.71.8.909

Cited by 225 publications

(141 citation statements)

References 7 publications

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“…GeoEye does not provide per-pixel look angles, instead a sensor orientation model, or rational function model (RFM) is used to describe the object-to-image space transformation mathematically. RFM parameters derived from a rigorous sensor model are supplied with the imagery and are termed RPCs [36,37].…”

Section: Ikonos Stereo Imagerymentioning

confidence: 99%

Deciphering the Precision of Stereo IKONOS Canopy Height Models for US Forests with G-LiHT Airborne LiDAR

et al. 2014

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Few studies have evaluated the precision of IKONOS stereo data for measuring forest canopy height. The high cost of airborne light detection and ranging (LiDAR) data collection for large area studies and the present lack of a spaceborne instrument lead to the need to explore other low cost options. The US Government currently has access to a large archive of commercial high-resolution imagery, which could be quite valuable to forest structure studies. At 1 m resolution, we here compared canopy height models (CHMs) and height data derived from Goddard's airborne LiDAR Hyper-spectral and Thermal Imager (G-LiHT) with three types of IKONOS stereo derived digital surface models (DSMs) that estimate CHMs by subtracting National Elevation Data (NED) digital terrain models (DTMs). We found the following in three different forested regions of the US after excluding heterogeneous and disturbed forest samples: (1) G-LiHT DTMs were highly correlated with NED DTMs with R 2 > 0.98 and root mean square errors (RMSEs) < 2.96 m; (2) when using one visually identifiable ground control point (GCP) from NED, G-LiHT DSMs and IKONOS DSMs had R 2 > 0.84 and RMSEs of 2.7 to 4.1 m; and (3) one GCP CHMs for two study sites had R 2 > 0.7 and RMSEs of 2.6 to 3 m where data were collected less than four years apart. Our results suggest that IKONOS stereo data are a useful LiDAR alternative where high-quality DTMs are available.

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Section: Ikonos Stereo Imagerymentioning

confidence: 99%

Deciphering the Precision of Stereo IKONOS Canopy Height Models for US Forests with G-LiHT Airborne LiDAR

et al. 2014

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“…Therefore, for most satellite stereo imagery, the orientation procedure is essential, and it is almost equal to the refinement of the RPCs. The additional biascompensation bundle block adjustment is a convenient and accurate method to refine the RPCs and remove the bias (Grodecki and Dial, 2003;Fraser and Hanley, 2005). As we know, the limitation of this method is the requirement of GCPs.…”

Section: Global Relative Orientationmentioning

confidence: 99%

“…The bias-compensated bundle block adjustment is an absolute orientation procedure and, practically, the minimum number of GCPs should be 4 to 6 (Fraser and Hanley, 2005).…”

Section: Relative Bias-compensated Modelmentioning

confidence: 99%

Relative Orientation and Modified Piecewise Epipolar Resampling for High Resolution Satellite Images

Gong

Fritsch

2017

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

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ABSTRACT:High resolution, optical satellite sensors are boosted to a new era in the last few years, because satellite stereo images at half meter or even 30cm resolution are available. Nowadays, high resolution satellite image data have been commonly used for Digital Surface Model (DSM) generation and 3D reconstruction. It is common that the Rational Polynomial Coefficients (RPCs) provided by the vendors have rough precision and there is no ground control information available to refine the RPCs. Therefore, we present two relative orientation methods by using corresponding image points only: the first method will use quasi ground control information, which is generated from the corresponding points and rough RPCs, for the bias-compensation model; the second method will estimate the relative pointing errors on the matching image and remove this error by an affine model. Both methods do not need ground control information and are applied for the entire image. To get very dense point clouds, the Semi-Global Matching (SGM) method is an efficient tool. However, before accomplishing the matching process the epipolar constraints are required. In most conditions, satellite images have very large dimensions, contrary to the epipolar geometry generation and image resampling, which is usually carried out in small tiles. This paper also presents a modified piecewise epipolar resampling method for the entire image without tiling. The quality of the proposed relative orientation and epipolar resampling method are evaluated, and finally sub-pixel accuracy has been achieved in our work.

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“…This error arises due to the errors in the satellite attitude and Ephemeris determination as well as due to the limited accuracy of sensor orientation described by the RPC models as compared to the rigorous sensor model (Fraser and Hanley, 2005;Grodecki and Dial, 2003). In this work, only the relative RPC error (De Franchis et al, 2014) is removed so that the corresponding points between the two images lie on the corresponding epipolar lines.…”

Section: Relative Rpc Errormentioning

confidence: 99%

Satellite Stereo Based Digital Surface Model Generation Using Semi Global Matching in Object and Image Space

Ghuffar¹

2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:This paper presents methodology and evaluation of Digital Surface Models (DSM) generated from satellite stereo imagery using Semi Global Matching (SGM) applied in image space and georeferenced voxel space. SGM is a well known algorithm, used widely for DSM generation from airborne and satellite imagery. SGM is typically applied in the image space to compute disparity map corresponding to a stereo image pair. As a different approach, SGM can be applied directly to the georeferenced voxel space similar to the approach of volumetric multi-view reconstruction techniques. The matching in voxel space simplifies the DSM generation pipeline because the stereo rectification and triangulation steps are not required. For a comparison, the complete pipeline for generation of DSM from satellite pushbroom sensors is also presented. The results on the ISPRS satellite stereo benchmark using Worldview stereo imagery of 0.5m resolution shows that the SGM applied in image space produce slightly better results than its object space counterpart. Furthermore, a qualitative analysis of the results on Worldview-3 stereo and Pleiades tri-stereo images are presented.

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Bias-compensated RPCs for Sensor Orientation of High-resolution Satellite Imagery

Cited by 225 publications

References 7 publications

Deciphering the Precision of Stereo IKONOS Canopy Height Models for US Forests with G-LiHT Airborne LiDAR

Deciphering the Precision of Stereo IKONOS Canopy Height Models for US Forests with G-LiHT Airborne LiDAR

Relative Orientation and Modified Piecewise Epipolar Resampling for High Resolution Satellite Images

Satellite Stereo Based Digital Surface Model Generation Using Semi Global Matching in Object and Image Space

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