scholarly journals A Generic Bundle Adjustment Methodology for Indirect RPC Model Refinement of Satellite Imagery

2021 ◽  
Vol 11 ◽  
pp. 344-373
Author(s):  
Roger Marí ◽  
Carlo de Franchis ◽  
Enric Meinhardt-Llopis ◽  
Jérémy Anger ◽  
Gabriele Facciolo
Keyword(s):  
Satellite Imagery ◽  
Bundle Adjustment ◽  
Model Refinement

DEM-Aided Bundle Adjustment With Multisource Satellite Imagery: ZY-3 and GF-1 in Large Areas

2016 ◽  
Vol 13 (6) ◽  
pp. 880-884 ◽  
Author(s):  
Maoteng Zheng ◽  
Yongjun Zhang
Keyword(s):  
Satellite Imagery ◽  
Bundle Adjustment

scholarly journals Geometric Accuracy Study of Orthorectification Based on Sensor Model Refinement in Imagery Subset Using ORFEO Toolbox (OTB)

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Andri Suprayogi ◽  
Nurhadi Bashit
Keyword(s):  
Remote Sensing ◽  
Satellite Imagery ◽  
Ground Control ◽  
Surface Model ◽  
Control Points ◽  
Geometric Accuracy ◽  
Model Refinement ◽  
Full Extent ◽  
Sensor Model ◽  
Ground Control Points

Large scale base map can be obtained by various methods, one of them is orthorectification process of remote sensing satellite imagery to eliminate the relief displacement caused by height variation of earth surface. To obtain a  map images with good quality,  it requires additional data such as sensor model in the form of rational polynomial coefficients (RPC), surface model data, and ground control points Satellite imageries with high resolution  file size are relatively large.  In order to process them,  high specification of hardwares were required. To overcome this by cutting only a portion of the images, based on certain study areas were suffer from of georeference lost so it would not be able to orthorectified. On the other hand,  in several remote sensing software such as ESA SNAP and Orfeo Toolbox (OTB)  subset or pixel extraction from satellite imagery,  preserve the imagery geometric sensor models. This research aimed at geometric accuracy of orthorectification carried out in a single scene of Pleiades Imagery within the Kepahiang Subdistrict, located at Kepahiang Regency, Bengkulu Province, by using DEMNAS and the imagery refined sensor mode, and ground control points taken using GPS Survey. Related with the raw imagery condition which consists of Panchromatic and multispectral bands, this study were separated to assembly, pan sharpening , and sensor model refinement stages prior to orthorectification carried out both in the original or full extent imagery and the result of subset extent imagery. After  these processses taken place, we measure the accuracy of each full and subset imagery.These procedures were carried out using Orfeo toolbox 6.6.0 in the Linux Mint 19 Operating system. From the process log, running time in total  were 7814.518  second for the full extent and 4321.95 seconds for the subset processess. And as a big data process, the total of full extent imageries was 83.15 GB  while the subset size  was  only 30.73 GB.  The relative accuracy of the full extent and its subset imagery were 0.431 meters. Accuracy of the  sensor model refinement process are  1.217 meters and 1.550 meters with GCP added, while the accuracu of  the orthorectifications results were  0.416 meters and 0.751 meters by using ICP.  Variation of execution time may caused by the data input size and complexity of the mathematical process carried out in each stages. Meanwhile,  the variation of accuracy may  caused by the check or control points placements above satellite Imagery which suffer from uncertainty when dealing with  the sub-pixel position or under 0.5 meters.

scholarly journals Combined Geometric Positioning and Performance Analysis of Multi-Resolution Optical Imageries from Satellite and Aerial Platforms Based on Weighted RFM Bundle Adjustment

2021 ◽  
Vol 13 (4) ◽  
pp. 620
Author(s):  
Wenping Song ◽  
Shijie Liu ◽  
Xiaohua Tong ◽  
Changling Niu ◽  
Zhen Ye ◽  
...  
Keyword(s):  
Performance Analysis ◽  
Satellite Imagery ◽  
Bundle Adjustment ◽  
Phase Correlation ◽  
Engineering Applications ◽  
Positioning Accuracy ◽  
Optical Images ◽  
Practical Engineering ◽  
Aerial Platforms ◽  
And Performance

Combined geometric positioning using images with different resolutions and imaging sensors is being increasingly widely utilized in practical engineering applications. In this work, we attempt to perform the combined geometric positioning and performance analysis of multi-resolution optical images from satellite and aerial platforms based on weighted rational function model (RFM) bundle adjustment without using ground control points (GCPs). Firstly, we introduced an integrated image matching method combining least squares and phase correlation. Next, for bundle adjustment, a combined model of the geometric positioning based on weighted RFM bundle adjustment was derived, and a method for weight determination was given to make the weights of all image points variable. Finally, we conducted experiments using a case study in Shanghai with ZiYuan-3 (ZY-3) satellite imagery, GeoEye-1 satellite imagery, and Digital Mapping Camera (DMC) aerial imagery to validate the effectiveness of the proposed weighted method, and to investigate the positioning accuracy by using different combination scenarios of multi-resolution heterogeneous images. The experimental results indicate that the proposed weighted method is effective, and the positioning accuracy of different combination scenarios can give a good reference for the combined geometric positioning of multi-stereo heterogeneous images in future practical engineering applications.

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