Improving Orthorectification of UAV-Based Push-Broom Scanner Imagery Using Derived Orthophotos From Frame Cameras

Habib, Ayman; Xiong, Weifeng; He, Fenghua; Yang, Hsiuhan Lexie; Crawford, Melba M.

doi:10.1109/jstars.2016.2520929

Cited by 57 publications

(59 citation statements)

References 27 publications

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“…The camera systems are designed to be as small as possible and therefore, the technical specification may suffer in comparison to bigger camera systems. Bigger sensors have often a push-broom scanner, which makes it possible to acquire images of high resolution, but need sophisticated methods for a reasonable orthorectification, while snapshot sensors on the other hand have a low resolution (Habib et al, 2017). Additionally, a UAV based sensor does not have space for a cooling system, which degrades the radiometric performance.…”

Section: Data Fusionmentioning

confidence: 99%

Concept for Classifying Facade Elements Based on Material, Geometry and Thermal Radiation Using Multimodal Uav Remote Sensing

Ilehag

Schenk

Hinz

2017

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

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ABSTRACT:This paper presents a concept for classification of facade elements, based on the material and the geometry of the elements in addition to the thermal radiation of the facade with the usage of a multimodal Unmanned Aerial Vehicle (UAV) system. Once the concept is finalized and functional, the workflow can be used for energy demand estimations for buildings by exploiting existing methods for estimation of heat transfer coefficient and the transmitted heat loss. The multimodal system consists of a thermal, a hyperspectral and an optical sensor, which can be operational with a UAV. While dealing with sensors that operate in different spectra and have different technical specifications, such as the radiometric and the geometric resolution, the challenges that are faced are presented. Addressed are the different approaches of data fusion, such as image registration, generation of 3D models by performing image matching and the means for classification based on either the geometry of the object or the pixel values. As a first step towards realizing the concept, the result from a geometric calibration with a designed multimodal calibration pattern is presented.

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Section: Data Fusionmentioning

confidence: 99%

Concept for Classifying Facade Elements Based on Material, Geometry and Thermal Radiation Using Multimodal Uav Remote Sensing

Ilehag

Schenk

Hinz

2017

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

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“…The transformation function relating the partially-rectified hyperspectral and RGB-based orthophotos is based on the proposed methodology in [5]. Following is a brief theoretical background for such a transformation function.…”

Section: Registration Of the Rgb And Partially-rectified Hyperspectramentioning

confidence: 99%

“…The scaling error δλ i in Equation (4) represents the cumulative impact of the erroneous scanner position and orientation on the scale factor λ i . Equation (4) can be expanded to the form in Equation (5). As can be derived from Equation (3), λ i R m c r c i is equivalent to r m I − r m c .…”

Section: Registration Of the Rgb And Partially-rectified Hyperspectramentioning

confidence: 99%

“…Improved performance of integrated Global Navigation Satellite Systems (GNSS) and Inertial Navigation Systems (INS) together with the reduced cost of imaging sensors operating in different portions of the electromagnetic spectrum are among the main reasons for the growing interest in MMS for high throughput phenotyping. Among the possible MMS platforms, UAVs are now becoming competitive platforms for remotesensing-based phenotyping, as they can be easily and cost-effectively deployed while collecting geospatial data with higher temporal and spatial resolution than other platforms [5][6][7][8]. Thus, UAVs equipped with directly geo-referenced imaging sensors are also being used for these applications [9].…”

Section: Introductionmentioning

confidence: 99%

“…2016, 8,796 3 of 22 presented a computer-vision approach for the indirect geo-referencing of the hyperspectral scenes, which estimated a set of transformation parameters relating the reference frames of frame and hyperspectral imagery. In [5], a methodology was presented for improving the ortho-rectification of hyperspectral imagery in the presence of low-quality navigation information with the help of frame imagery using tie points and linear features. In this approach, a transformation function is developed to model the impact of residual artifacts in the direct geo-referencing information.…”

Section: Introductionmentioning

confidence: 99%

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Automated Ortho-Rectification of UAV-Based Hyperspectral Data over an Agricultural Field Using Frame RGB Imagery

et al. 2016

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Low-cost Unmanned Airborne Vehicles (UAVs) equipped with consumer-grade imaging systems have emerged as a potential remote sensing platform that could satisfy the needs of a wide range of civilian applications. Among these applications, UAV-based agricultural mapping and monitoring have attracted significant attention from both the research and professional communities. The interest in UAV-based remote sensing for agricultural management is motivated by the need to maximize crop yield. Remote sensing-based crop yield prediction and estimation are primarily based on imaging systems with different spectral coverage and resolution (e.g., RGB and hyperspectral imaging systems). Due to the data volume, RGB imaging is based on frame cameras, while hyperspectral sensors are primarily push-broom scanners. To cope with the limited endurance and payload constraints of low-cost UAVs, the agricultural research and professional communities have to rely on consumer-grade and light-weight sensors. However, the geometric fidelity of derived information from push-broom hyperspectral scanners is quite sensitive to the available position and orientation established through a direct geo-referencing unit onboard the imaging platform (i.e., an integrated Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS). This paper presents an automated framework for the integration of frame RGB images, push-broom hyperspectral scanner data and consumer-grade GNSS/INS navigation data for accurate geometric rectification of the hyperspectral scenes. The approach relies on utilizing the navigation data, together with a modified Speeded-Up Robust Feature (SURF) detector and descriptor, for automating the identification of conjugate features in the RGB and hyperspectral imagery. The SURF modification takes into consideration the available direct geo-referencing information to improve the reliability of the matching procedure in the presence of repetitive texture within a mechanized agricultural field. Identified features are then used to improve the geometric fidelity of the previously ortho-rectified hyperspectral data. Experimental results from two real datasets show that the geometric rectification of the hyperspectral data was improved by almost one order of magnitude.

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Hyperspectral imaging systems for corrosion detection from remotely operated vehicles

Thomas,

Gündel

2023

ce papers

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The detection of corrosion, especially in early stages, is a key factor for cost reduction in the maintenance of steel infrastructure. However, manual inspection is time consuming and takes considerable effort of people and equipment. Remotely operated vehicles with application‐specific sensors may overcome this problem. Novel sensing approaches like hyperspectral imaging (HSI) systems in combination with machine learning algorithms open new pathways for the rapid inspection of large surface areas in complex environments. In contrast to conventional RGB imaging, HSI contains both spatial and spectral reflectivity information over the complete visual spectral range and near infrared. This offers improved material characterization and classification possibilities using the chemical properties contained in the local reflection spectrum.This paper presents advantages and disadvantages of hyperspectral imaging systems for the detection of corrosion of steel infrastructure as well as suitable wavelength ranges for use with remotely operated vehicles. Furthermore, in‐field measurements with HSI for the inspection of corrosion on steel structures are shown.

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Improving Orthorectification of UAV-Based Push-Broom Scanner Imagery Using Derived Orthophotos From Frame Cameras

Cited by 57 publications

References 27 publications

Concept for Classifying Facade Elements Based on Material, Geometry and Thermal Radiation Using Multimodal Uav Remote Sensing

Concept for Classifying Facade Elements Based on Material, Geometry and Thermal Radiation Using Multimodal Uav Remote Sensing

Automated Ortho-Rectification of UAV-Based Hyperspectral Data over an Agricultural Field Using Frame RGB Imagery

Hyperspectral imaging systems for corrosion detection from remotely operated vehicles

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