Orthorectification of Planetary Linear Pushbroom Images Based on an Improved Back-Projection Algorithm

Geng, Xiurui; Xu, Qing; Lan, Chaozhen; Xing, Shu; Hou, Yifan; Lyu, Liang

doi:10.1109/lgrs.2018.2885086

Cited by 7 publications

(7 citation statements)

References 11 publications

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“…The two Chandrayaan-1 M3 images were acquired with summing mode and the macropixels value was 2. It is noted that the computational performance of this experiment was not as good as that presented in (Geng et al, 2018), due to that virtual machine was used in this test. However, the results still show that the computational efficiency of the developed method is much better than that of ISIS, due to the optimized ground-to-image transformation algorithm.…”

Section: Orthophotos Generation Resultsmentioning

confidence: 83%

“…ASP also uses the ISIS sensor model to process planetary images. However, it is noted that the computational efficiency of the ISIS pushbroom sensor model is unsatisfactory, especially in ground-to-image transformation algorithm (Geng et al, 2018). Additionally, to apply more powerful photogrammetric features, commercial photogrammetric workstation such as BAE Systems' SOCET SET is always adopted (Kirk et al, 2008;Kirk et al, 2017).…”

Section: Existing Pushbroom Sensor Modelmentioning

confidence: 99%

“…Therefore, the original CPP-based ground-to-image transformation algorithm was further improved. In short, the linear array with distortions is segmented into multiple line segments, and the exact CPP is determined using simple analytical geometric calculations (Geng et al, 2018).…”

Section: Ground-to-image Transformationmentioning

confidence: 99%

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A Generic Rigorous Sensor Model for Photogrammetric Processing of Pushbroom Planetary Images

Geng

Xing²,

Xu³

2019

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

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<p><strong>Abstract.</strong> Currently, each planetary exploration mission team always develops its own software modules to support the photogrammetric processing of planetary images, and as a result of that the main drawbacks are lacking software reusability and the high cost of software development and maintenance. This is mainly due to that there is lack of a highly universal sensor model in the planetary mapping community. This paper presents a generic rigorous sensor model (RSM) for the photogrammetric processing of pushbroom planetary images. The main contributions of this paper include: (1) the implementation details of the generic RSM; (2) the optimized coordinates transformation methods between 3D ground points and 2D image points for linear pushbroom images; (3) a pipeline to acquire exterior orientation (EO) parameters for each planetary image. The generic RSM is developed based on the methodology used in airborne linear scanners ADS40. Specifically, the generic RSM comprises of a camera file and an orientation data file for each image. The camera file stores each detector’s calibrated image coordinates and the orientation data file contains each scan line’s EO parameters, such that the RSM can perform coordinates transformation among pixel coordinates, focal plane coordinates and ground coordinates. Furthermore, the generic RSM supports varying exposure time, summing mode and image distortions, which are typical problems that need to be solved in planetary mapping. We tested the generic RSM with Lunar Reconnaissance Orbiter (LRO) Narrow Angle Camera (NAC), Chandrayaan-1 Moon Mineralogy Mapper (M3) and Mars Express (MEX) High Resolution Stereo Camera (HRSC) images. The geometric accuracy and computational efficiency of the developed generic RSM were compared with the famous planetary mapping software, namely Integrated System for Imagers and Spectrometers (ISIS). The experimental results demonstrate that the generic RSM has the merits of processing various types of pushbroom planetary images with a unified way and decreasing the software development and maintenance burden. Moreover, the developed generic RSM significantly improves the computational efficiency of orthophoto generation and tie points extraction for pushbroom planetary images.</p>

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Section: Orthophotos Generation Resultsmentioning

confidence: 83%

Section: Existing Pushbroom Sensor Modelmentioning

confidence: 99%

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A Generic Rigorous Sensor Model for Photogrammetric Processing of Pushbroom Planetary Images

Geng

Xing²,

Xu³

2019

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

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“…To evaluate the computational efficiency, we compared the proposed method with two representative methods, namely, the cutting‐edge CPP‐based method and the classical bisection method. It is noted that the CPP‐based method delivers high computational efficiency for the linear pushbroom images without distortions (Geng et al, ; Wang et al, ), whereas the bisection method is widely used but shows relatively lower efficiency. The results are shown in Figure .…”

Section: Resultsmentioning

confidence: 99%

“…However, in the case of a linear array camera with distortions, the CPP of the scan line becomes a 3‐D curved surface instead of a 3‐D plane. Consequently, to apply the CPP‐based method, the curved shape linear array should be segmented into multiple short line segments, such that the exact CPP corresponding to the ground point can be determined (Geng et al, ). These additional procedures cause the CPP‐based method to be relatively difficult to implement for the linear pushbroom images with distortions.…”

Section: Introductionmentioning

confidence: 99%

A Robust Ground‐to‐Image Transformation Algorithm and Its Applications in the Geometric Processing of Linear Pushbroom Images

Geng

Xing

et al. 2019

Earth and Space Science

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Linear array cameras are widely used in the fields of aerial and space remote sensing. The ground‐to‐image transformation plays a significant role in the geometric processing procedures of linear pushbroom images, which is time‐consuming due to multiple iterative calculations. Moreover, the detectors of the linear array may exhibit a curved shape due to distortions, resulting in a more complex ground‐to‐image transformation. This paper presents a novel ground‐to‐image transformation algorithm for linear pushbroom images based on a rigorous sensor model. We regard the distance between the back‐projected image point and the curved shape linear array as the “generalized distance.” The idea of generalized distance prediction was developed to efficiently determine the best scan line corresponding to the ground point. The plane analytic geometry is employed to solve the practical problems of the ground‐to‐image transformation, including the iterative direction, convergence condition, and subpixel interpolation. The applications of the proposed method in orthorectification and image matching were investigated. The proposed method was comprehensively tested using airborne images, Earth observation satellite images, and planetary images. The experimental results demonstrate that the proposed method (1) delivers high accuracy (better than 1 × 10−4 pixels) and efficiency, (2) is better than the cutting‐edge method based on the geometric constraints of central perspective plane for the linear pushbroom images with distortions, and (3) provides promising applications for generating orthophotos and image matching. The proposed method is easy to implement and efficient, which can greatly enhance the geometric processing abilities for various types of linear pushbroom images.

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A fast non-iterative method for the object to image space best scanline determination of spaceborne linear array pushbroom images

Nezhad

Zoej

Ghorbanian

2021

Advances in Space Research

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Orthorectification of Planetary Linear Pushbroom Images Based on an Improved Back-Projection Algorithm

Cited by 7 publications

References 11 publications

A Generic Rigorous Sensor Model for Photogrammetric Processing of Pushbroom Planetary Images

A Generic Rigorous Sensor Model for Photogrammetric Processing of Pushbroom Planetary Images

A Robust Ground‐to‐Image Transformation Algorithm and Its Applications in the Geometric Processing of Linear Pushbroom Images

A fast non-iterative method for the object to image space best scanline determination of spaceborne linear array pushbroom images

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