Semi-automatic geometric correction of airborne hyperspectral push-broom images using ground control points and linear features

Hao, Fang; Hu, Binlin; Yu, Zhenglei; Xu, Hongwei; He, Chu; Li, Aihua; Liu, Yinnian

doi:10.1080/01431161.2018.1455237

Cited by 3 publications

(4 citation statements)

References 24 publications

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“…These aspects can firstly be improved by developing an improved sliding system and refining its technical design. However, greater advantage is envisaged in exploring manual or automatic pushbroom HI rectification techniques through the incorporation of overlapping RGB orthomosaics, also known as co-registration [81][82][83]. This approach co-registers the hyperspectral imagery based on a reference RGB orthomosaic through image matching procedures (e.g., feature matching and transformation based on matching points [28]).…”

Section: System Performance and Future Developmentsmentioning

confidence: 99%

“…By taking advantage of the referenceable sea-ice surface and co-registration methods we could then theoretically develop algorithms analogous to aerial HI algorithms based on the scaled RGB orthomosaics, the partially rectified HI scans and the acquired consumer-grade IMU data [37,81,82]. These future developments will aim to support the geometric correction of distortions caused by the dynamics of the HI frame, such as the lagging instances (Figure 6c).…”

Section: System Performance and Future Developmentsmentioning

confidence: 99%

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An Under-Ice Hyperspectral and RGB Imaging System to Capture Fine-Scale Biophysical Properties of Sea Ice

et al. 2019

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Sea-ice biophysical properties are characterized by high spatio-temporal variability ranging from the meso-to the millimeter scale. Ice coring is a common yet coarse point sampling technique that struggles to capture such variability in a non-invasive manner. This hinders quantification and understanding of ice algae biomass patchiness and its complex interaction with some of its sea ice physical drivers. In response to these limitations, a novel under-ice sled system was designed to capture proxies of biomass together with 3D models of bottom topography of land-fast sea-ice. This system couples a pushbroom hyperspectral imaging (HI) sensor with a standard digital RGB camera and was trialed at Cape Evans, Antarctica. HI aims to quantify per-pixel chlorophyll-a content and other ice algae biological properties at the ice-water interface based on light transmitted through the ice. RGB imagery processed with digital photogrammetry aims to capture under-ice structure and topography. Results from a 20 m transect capturing a 0.61 m wide swath at sub-mm spatial resolution are presented. We outline the technical and logistical approach taken and provide recommendations for future deployments and developments of similar systems. A preliminary transect subsample was processed using both established and novel under-ice bio-optical indices (e.g., normalized difference indexes and the area normalized by the maximal band depth) and explorative analyses (e.g., principal component analyses) to establish proxies of algal biomass. This first deployment of HI and digital photogrammetry under-ice provides a proof-of-concept of a novel methodology capable of delivering non-invasive and highly resolved estimates of ice algal biomass in-situ, together with some of its environmental drivers. Nonetheless, various challenges and limitations remain before our method can be adopted across a range of sea-ice conditions. Our work concludes with suggested solutions to these challenges and proposes further method and system developments for future research.

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Section: System Performance and Future Developmentsmentioning

confidence: 99%

Section: System Performance and Future Developmentsmentioning

confidence: 99%

An Under-Ice Hyperspectral and RGB Imaging System to Capture Fine-Scale Biophysical Properties of Sea Ice

et al. 2019

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“…The original RPC with the affine transformation parameters, whose initial values are set to zero, is used to calculate the space coordinates of the corresponding image points within each stereo scene. This calculation is conducted through space intersection based on Equation (2).…”

Section: ) Space Intersection Within Each Stereo Scenementioning

confidence: 99%

“…Space resection for each image is then performed to solve the affine transformation parameters, namely, the unknowns (e 0 , e 1 , e 2 , f 0 , f 1 , f 2 ). All the observations (r, c) and the corresponding ''virtual control points''X are used to construct linear equations using Equations (2). The affine transformation parameters of satellite images are solved and updated through the least squares method.…”

Section: ) Space Resection For Each Imagementioning

confidence: 99%

Adaptive Re-weighted Block Adjustment for Multi-Coverage Satellite Stereo Images without Ground Control Points

et al. 2019

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Georeferencing satellite imagery is the basis for mapping and other subsequent processing in photogrammetry and remote sensing. Traditional georeferencing methods, which require adequate and well-distributed ground control points (GCPs), are time-consuming, costly, constantly cumbersome and inefficient. This study proposes a method of adaptive re-weighted block adjustment without GCPs for satellite stereo images. Furthermore, an approach of using multi-coverage images to improve the direct georeferencing accuracy is also investigated. The bias-compensated rational function model with affine transformation parameters is used as the adjustment mathematical model. The ''weighted virtual control points'' are introduced as constraints in the adjustment. Space intersection and resection are executed iteratively to solve the accurate affine transformation parameters. A total of 722 three-line array stereo scenes of Chinese Mapping Satellite-1 images captured from December 2010 to March 2016, which cover the entire Shandong Province of China (about 158,000 km 2 ) nearly 10 times in space, are used as experimental data to evaluate the performance of the proposed method. Experiment results demonstrate that the proposed method can effectively eliminate the systematic errors of images. Moreover, the additional comparison with experiments of three groups of mono-coverage images indicates that the redundant observations from multi-coverage images can significantly improve the direct georeferencing accuracy, more specifically, from 13.69-16.02 m to 11.09 m in the horizontal direction, and from 16.39-29.27 m to 8.47 m in the vertical direction.INDEX TERMS Georeferencing satellite imagery, block adjustment, without ground control points (GCPs), multi-coverage satellite images, weighted virtual control points.

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A new approach for geometric correction of UAV-based pushbroom images through the processing of simultaneously acquired frame images

2022

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Semi-automatic geometric correction of airborne hyperspectral push-broom images using ground control points and linear features

Cited by 3 publications

References 24 publications

An Under-Ice Hyperspectral and RGB Imaging System to Capture Fine-Scale Biophysical Properties of Sea Ice

An Under-Ice Hyperspectral and RGB Imaging System to Capture Fine-Scale Biophysical Properties of Sea Ice

Adaptive Re-weighted Block Adjustment for Multi-Coverage Satellite Stereo Images without Ground Control Points

A new approach for geometric correction of UAV-based pushbroom images through the processing of simultaneously acquired frame images

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