Epipolar Resampling of Space-borne Linear Array Scanner Scenes Using Parallel Projection

Morgan, Michel; Kim, Kyung-Ok; Jeong, Seri; Habib, Ayman

doi:10.14358/pers.72.11.1255

Cited by 52 publications

(55 citation statements)

References 2 publications

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“…Like the image space-based method, the PRP method also extracts control points from the original image space but assigns the control points' coordinates to new coordinates on a PRP in object space instead of image space. This method does not require any ground control points, which is essential to the method suggested by Morgan et al [9]. And this method may not cause a non-orthogonal axis in the object space.…”

Section: Object Space-based Methodsmentioning

confidence: 99%

Unified piecewise epipolar resampling method for pushbroom satellite images

Koh

Yang

2016

J Image Video Proc.

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Computational stereo is in the fields of computer vision and photogrammetry. In the computational stereo and surface reconstruction paradigms, it is very important to achieve appropriate epipolar constraints during the camera-modeling step of the stereo image processing. It has been shown that the epipolar geometry of linear pushbroom imagery has a hyperbola-like shape because of the non-coplanarity of the line of sight vectors. Several studies have been conducted to generate resampled epipolar image pairs from linear pushbroom satellites images; however, the currently prevailing methods are limited by their pixel scales, skewed axis angles, or disproportionality between x-parallax disparities and height. In this paper, a practical and unified piecewise epipolar resampling method is proposed to generate stereo image pairs with zero y-parallax, a square pixel scale, and proportionality between x-parallax disparity and height. Furthermore, four criteria are suggested for performance evaluations of the prevailing methods, and experimental results of the method are presented based on the suggested criteria. The proposed method is shown to be equal to or an improvement upon the prevailing methods.

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Section: Object Space-based Methodsmentioning

confidence: 99%

Unified piecewise epipolar resampling method for pushbroom satellite images

Koh

Yang

2016

J Image Video Proc.

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“…As we all know, the epipolar geometric constraint is always used in image matching, both for frame images and linear pushbroom images [36][37][38]. However, it is difficult to determine the exact epipolar line equation for linear pushbroom imagery.…”

Section: Image Matching On Approximate Orthophotosmentioning

confidence: 99%

“…However, it is difficult to determine the exact epipolar line equation for linear pushbroom imagery. Moreover, the prerequisite of epipolar resampling for linear cameras [37] may not be suitable for HRSC linear pushbroom imagery, which has variable line exposure duration. The projection trajectory method is always used to establish the epipolar line for linear pushbroom imagery.…”

Section: Image Matching On Approximate Orthophotosmentioning

confidence: 99%

A Novel Pixel-Level Image Matching Method for Mars Express HRSC Linear Pushbroom Imagery Using Approximate Orthophotos

Geng¹,

Xu²,

Xing³

et al. 2017

Remote Sensing

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Mars topographic data, such as digital orthophoto maps (DOMs) and digital elevation models (DEMs) are essential to planetary science and exploration missions. The main objective of our study is to generate a higher resolution DEM using the Mars Express (MEX) High Resolution Stereo Camera (HRSC). This paper presents a novel pixel-level image matching method for HRSC linear pushbroom imagery. We suggest that image matching firstly be carried out on the approximate orthophotos. Then, the matched points are converted to the original images for forward intersection. The proposed method adopts some practical strategies such as hierarchical image matching and normalized cross-correlation (NCC). The characteristic strategies are: (1) the generation of a DEM and a DOM at each pyramid level; (2) the use of the generated DEM at the current pyramid level as reference data to generate approximate orthophotos at the next pyramid level; and (3) the use of the ground point coordinates of orthophotos to estimate the approximate positions of conjugate points. Hence, the refined DEM is used in the image rectification process, and pixel coordinate displacements of conjugate points on the approximate orthophotos will become smaller and smaller. Four experimental datasets acquired by the HRSC were used to verify the proposed method. The generated DEM was compared with the HRSC Level-4 DEM product. Experimental results demonstrate that an accurate and precise Mars DEM can be generated with the proposed method. The approximate positions of the conjugate points can be estimated with an accuracy of three pixels at the original image resolution level. Though slight systematic errors of about two pixels were observed, the generated DEM results show good consistency with the HRSC Level-4 DEM.

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“…Considering the rather short acquisition time of the imagery (for example, about 1 s for an IKONOS scene), the velocity, and orientation of the sensor can be assumed constant during the capture of the scene [29][30][31][32]. Hence, modeling the along-track image component via the 3D affine model is easy [32][33][34]. Implicit in the model are two individual projections, one scaled-orthogonal, and the other skew-parallel (Figure 2a).…”

Section: The Geometry Of Linear Pushbroom Imagingmentioning

confidence: 99%

A Knowledge-Based Search Strategy for Optimally Structuring the Terrain Dependent Rational Function Models

2017

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Abstract:Identifying the optimal structure of terrain dependent Rational Function Models (RFMs) not only decreases the number of Ground Control Points (GCPs) required, but also increases the accuracy of the model, by reducing the multi-collinearity of Rational Polynomials Coefficients (RPCs) and avoiding the ill-posed problem. Global optimization algorithms such as Genetic Algorithm (GA), evaluate the different combinations of parameters effectively. Therefore, they have a high ability to detect the optimal structure of RFMs. However, one drawback of these algorithms is their high computation cost. This article proposes a knowledge-based search strategy to overcome this deficiency. The backbone of the proposed method relies on the technical knowledge about the geometric condition of image at the time of acquisition, as well as the effect of external factors such as terrain relief on the image. This method was evaluated on four different datasets, including a SPOT-1A, a SPOT-1B, an IKONOS-Geo image, and a GeoEye-Geo imagery, using various number of GCPs. Experimental results demonstrate the efficiency of the proposed method to achieve a sub-pixel accuracy using few GCPs (only 4-6 points) in all datasets. The results also indicate that the proposed method improves the computation speed by 140 times when comparing with GA.

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Epipolar Resampling of Space-borne Linear Array Scanner Scenes Using Parallel Projection

Cited by 52 publications

References 2 publications

Unified piecewise epipolar resampling method for pushbroom satellite images

Unified piecewise epipolar resampling method for pushbroom satellite images

A Novel Pixel-Level Image Matching Method for Mars Express HRSC Linear Pushbroom Imagery Using Approximate Orthophotos

A Knowledge-Based Search Strategy for Optimally Structuring the Terrain Dependent Rational Function Models

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