Multiscale Image Matching for Automated Calibration of UAV-Based Frame and Line Camera Systems

Hasheminasab, Seyyed Meghdad; Zhou, Tian; LaForest, Lisa; Habib, Ayman

doi:10.1109/jstars.2021.3062573

Cited by 7 publications

(3 citation statements)

References 28 publications

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“…Empirical airborne test flights in a calibration field have shown how block geometry influences the estimated calibration parameters and how consistent the parameters from lab calibration can be reproduced (Cramer et al 2017). Hasheminasab et al (2021) presents automated geometric calibration strategies for UAV-based frame and line camera systems to estimate accurate system calibration parameters without the need for ground control points or manual measurements of tie points.…”

Section: Methodsmentioning

confidence: 99%

Effect of Camera Calibration Refreshing on Orthophoto Position Accuracy in UAV Mapping

Sahin

2023

Turk J Remote Sens GIS

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Unmanned aerial vehicles (UAVs) are autonomous or remote control controlled air vehicles without a pilot. UAVs are aerial platforms capable of carrying non-metric photogrammetric equipment. In this study; the effect of two different calibration values of the camera available on the DJI Phantom 4 Pro equipment to the ortho-photo maps obtained from two different flight heights was investigated. An area within the campus of Gebze Technical University was chosen as a study area. PI 3000 software was used to calibrate the camera and the differences between the calculated parameters and the conventional parameters were determined. Also, the effect of the parameters on position accuracy was investigated. In the photogrammetric stereo model, the rms of Z depends on the picture scale, flight height, base length and the measurement accuracy of image coordinates. Since the measurement accuracy of the image coordinates x, y is also affected by the calibration accuracy, the calibration field independent of the Z value can be used. Geo-referencing and field measurements of the orthophotos produced by the GPS and measurement of the work area from two different heights with UAVs. Office work is the part where orthophotos are produced, georeferenced and analyzed with GPS coordinates of control points. The data obtained in the study reduces the rms value when recalibration is performed at a low flight altitude. However, a similar result could not be obtained for 120 meters flight altitude.

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Section: Methodsmentioning

confidence: 99%

Effect of Camera Calibration Refreshing on Orthophoto Position Accuracy in UAV Mapping

Sahin

2023

Turk J Remote Sens GIS

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“…Next, SIFT algorithm is applied on all partially ortho-rectified images/scenes. In this step, geolocation information of the orthorectified images/scenes is used to reduce the matching search space by conducting a window-based image matching strategy (Hasheminasab et al, 2021). As a result of this step, conjugate points between overlapping RGB images, HS scenes, and RGB image/HS scenes are identified.…”

Section: Methodsmentioning

confidence: 99%

Multi-Modal Triangulation for in-Situ Boresight Calibration of Frame and Line Cameras Onboard GNSS/Ins-Assisted Uavs

Hasheminasab

Zhou

Habib

2022

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

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Abstract. Unmanned aerial vehicles (UAVs) equipped with integrated global navigation satellite systems/inertial navigation systems (GNSS/INS) together with RGB and hyperspectral (HS) cameras have become popular data acquisition tool for several applications. To derive accurately georeferenced products from such systems, the spatial and rotational offset between the onboard sensors and the GNSS/INS unit must be determined. While the spatial relationship can be measured manually, establishing the angular offset – i.e., boresight angles – is more challenging and requires a calibration strategy. Given that the majority of RGB cameras are based on frame imaging mechanism, boresight calibration of these sensors is usually conducted through automated triangulation of overlapping images. On the other hand, most of current HS cameras are based on push-broom technology – also known as line cameras – which capture 1D images at a time. Consequently, automated triangulation of these non-overlapping images is not possible and thus, current boresight calibration strategies for HS cameras are based on calibration missions where special targets are deployed in the study site and are manually measured in the imagery. Although boresight calibration missions can lead to accurate system calibration parameters, they are expensive and labor intensive activities. To address these limitations and motivated by the new trend of UAVs equipped with both RGB and HS cameras, this study proposes a multi-modal triangulation approach to conduct an in-situ boresight calibration for the two cameras, simultaneously. Experimental results over an agricultural field and an urban area show that the proposed approach results in orthophotos with high visual quality and geolocation accuracy.

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“…(Goel et al, 2022) combined extracted SURF (Speed-Up Robust Features) and FLANN (Fast Library for Approximate Nearest Neighbours) feature matcher to improve the accuracy of geo-localization. (Hasheminasab et al, 2021) improved SIFT (Scale-Invariant Feature Transform) with image consistency check to realize the UAV image geo-localization with DOM. However, the above improvements on existing handcrafted features still retain the limitations for images with large viewpoint differences.…”

Section: Related Workmentioning

confidence: 99%

Uav Large Oblique Image Geo-Localization Using Satellite Images in the Dense Buildings Area

Luo,

2023

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. For UAV large oblique image geo-localization in the dense buildings area, there are still two main challenges. One is the presence of obvious occlusion and large viewpoint differences in UAV images, and the other arises from the fact that reference images, particularly orthographic satellite images, lack façade information of man-made structures (such as buildings and roads), which is crucial for UAV large oblique images. Most of existing image-based geo-localization methods only address the first challenge, neglecting the interference brought by the second challenge, especially for UAV large oblique image geo-localization in the dense buildings area. Motivated by both these two challenges, we have proposed a novel method for UAV large oblique image geo-localization in the dense buildings areas, with the segments direction statistics (SDS) features and their histogram descriptors designed. By considering both the local and global features of man-made structures, the proposed method effectively addresses the significant information difference encountered in cross-view image matching. We conducted experiments on both the public UAV images dataset University-1652 and our own collected dataset of UAV large oblique long focal whiskbroom (LO-LF-W) images. Comparative analysis with state-of-the-art (SOTA) methods demonstrated that the proposed method improves the geo-localization accuracy by approximately 10%. Furthermore, the proposed method exhibits greater robustness to noise and changing orientation of reference images, making it particularly well-suited for dense buildings areas that pose challenges for existing methods.

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Multiscale Image Matching for Automated Calibration of UAV-Based Frame and Line Camera Systems

Cited by 7 publications

References 28 publications

Effect of Camera Calibration Refreshing on Orthophoto Position Accuracy in UAV Mapping

Effect of Camera Calibration Refreshing on Orthophoto Position Accuracy in UAV Mapping

Multi-Modal Triangulation for in-Situ Boresight Calibration of Frame and Line Cameras Onboard GNSS/Ins-Assisted Uavs

Uav Large Oblique Image Geo-Localization Using Satellite Images in the Dense Buildings Area

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