Automated Georectification and Mosaicking of UAV-Based Hyperspectral Imagery from Push-Broom Sensors

Hyperspectral systems integrated on unmanned aerial vehicles (UAV) provide unique opportunities to conduct high-resolution multitemporal spectral analysis for diverse applications. However, additional time-consuming rectification efforts in postprocessing are routinely required, since geometric distortions can be introduced due to UAV movements during flight, even if navigation/motion sensors are used to track the position of each scan. Part of the challenge in obtaining high-quality imagery relates to the lack of a fast processing workflow that can retrieve geometrically accurate mosaics while optimizing the ground data collection efforts. To address this problem, we explored a computationally robust automated georectification and mosaicking methodology. It operates effectively in a parallel computing environment and evaluates results against a number of high-spatial-resolution datasets (mm to cm resolution) collected using a push-broom sensor and an associated RGB frame-based camera. The methodology estimates the luminance of the hyperspectral swaths and coregisters these against a luminance RGB-based orthophoto. The procedure includes an improved coregistration strategy by integrating the Speeded-Up Robust Features (SURF) algorithm, with the Maximum Likelihood Estimator Sample Consensus (MLESAC) approach. SURF identifies common features between each swath and the RGB-orthomosaic, while MLESAC fits the best geometric transformation model to the retrieved matches. Individual scanlines are then geometrically transformed and merged into a single spatially continuous mosaic reaching high positional accuracies only with a few number of ground control points (GCPs). The capacity of the workflow to achieve high spatial accuracy was demonstrated by examining statistical metrics such as RMSE, MAE, and the relative positional accuracy at 95% confidence level. Comparison against a user-generated georectification demonstrates that the automated approach speeds up the coregistration process by 85%.

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Accuracy of 3D Landscape Reconstruction without Ground Control Points Using Different UAS Platforms

Drones ◽

10.3390/drones4020013 ◽

2020 ◽

Vol 4 (2) ◽

pp. 13 ◽

Cited By ~ 4

Author(s):

Margaret Kalacska ◽

Oliver Lucanus ◽

J. Pablo Arroyo-Mora ◽

Étienne Laliberté ◽

Kathryn Elmer ◽

...

Keyword(s):

Low Cost ◽

Ground Control ◽

Unmanned Aerial Systems ◽

Control Points ◽

Model Errors ◽

Positional Accuracy ◽

Ground Control Points ◽

Digital Elevation ◽

High Level ◽

Aerial Systems

The rapid increase of low-cost consumer-grade to enterprise-level unmanned aerial systems (UASs) has resulted in the exponential use of these systems in many applications. Structure from motion with multiview stereo (SfM-MVS) photogrammetry is now the baseline for the development of orthoimages and 3D surfaces (e.g., digital elevation models). The horizontal and vertical positional accuracies (x, y and z) of these products in general, rely heavily on the use of ground control points (GCPs). However, for many applications, the use of GCPs is not possible. Here we tested 14 UASs to assess the positional and within-model accuracy of SfM-MVS reconstructions of low-relief landscapes without GCPs ranging from consumer to enterprise-grade vertical takeoff and landing (VTOL) platforms. We found that high positional accuracy is not necessarily related to the platform cost or grade, rather the most important aspect is the use of post-processing kinetic (PPK) or real-time kinetic (RTK) solutions for geotagging the photographs. SfM-MVS products generated from UAS with onboard geotagging, regardless of grade, results in greater positional accuracies and lower within-model errors. We conclude that where repeatability and adherence to a high level of accuracy are needed, only RTK and PPK systems should be used without GCPs.

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Avaliação de Desempenho no Georreferenciamento de Imagens do Sensor HR CCD (High Resolution Charge-Coupled Device) do Satélite CBERS-1

Pesquisas em Geociências ◽

10.22456/1807-9806.19548 ◽

2005 ◽

Vol 32 (2) ◽

pp. 81

Author(s):

RAFAEL PEREIRA ZANARDI ◽

SILVIA BEATRIZ ALVES ROLIM ◽

CLÁUDIO BIELENKI JÚNIOR ◽

CARLOS ALUISIO MESQUITA DE ALMEIDA

Keyword(s):

High Resolution ◽

Geometric Transformation ◽

Ground Control ◽

Control Points ◽

Differential Gps ◽

Charge Coupled Device ◽

Qualitative And Quantitative ◽

Ground Control Points ◽

Sampling Points ◽

Nearest Neighborhood

In this work it was analyzed the validation of CBERS-1 (China and Brazillian Earth Resourses Satellite) data related to qualitative and quantitative parameters that define the precision of its georeferencing. A topographical survey was carried out for the acquisition of ground control points spatially well distributed in the study area, employing differential GPS, aiming at the georeferencing of the image. Tests with different numbers of sampling points and several methods of Geometric Transformation and Resampling were made during the georeferencing. These results were statistically analyzed to determine the best method to georeference CBERS-1 images. It was verified that the first-degree polinomial transformation with nearest neighborhood resampling presented the best result, showing a precision of 18,52m.

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Evaluating the potential of post-processing kinematic (PPK) georeferencing for UAV-based structure- from-motion (SfM) photogrammetry and surface change detection

Earth Surface Dynamics ◽

10.5194/esurf-7-807-2019 ◽

2019 ◽

Vol 7 (3) ◽

pp. 807-827 ◽

Cited By ~ 19

Author(s):

He Zhang ◽

Emilien Aldana-Jague ◽

François Clapuyt ◽

Florian Wilken ◽

Veerle Vanacker ◽

...

Keyword(s):

Change Detection ◽

Structure From Motion ◽

Low Cost ◽

Post Processing ◽

Positional Accuracy ◽

Surface Change ◽

Ground Control Points ◽

Single Lens ◽

Surface Representations ◽

Uav Images

Abstract. Images captured by unmanned aerial vehicles (UAVs) and processed by structure-from-motion (SfM) photogrammetry are increasingly used in geomorphology to obtain high-resolution topography data. Conventional georeferencing using ground control points (GCPs) provides reliable positioning, but the geometrical accuracy critically depends on the number and spatial layout of the GCPs. This limits the time and cost effectiveness. Direct georeferencing of the UAV images with differential GNSS, such as PPK (post-processing kinematic), may overcome these limitations by providing accurate and directly georeferenced surveys. To investigate the positional accuracy, repeatability and reproducibility of digital surface models (DSMs) generated by a UAV–PPK–SfM workflow, we carried out multiple flight missions with two different camera–UAV systems: a small-form low-cost micro-UAV equipped with a high field of view (FOV) action camera and a professional UAV equipped with a digital single lens reflex (DSLR) camera. Our analysis showed that the PPK solution provides the same accuracy (MAE: ca. 0.02 m, RMSE: ca. 0.03 m) as the GCP method for both UAV systems. Our study demonstrated that a UAV–PPK–SfM workflow can provide consistent, repeatable 4-D data with an accuracy of a few centimeters. However, a few flights showed vertical bias and this could be corrected using one single GCP. We further evaluated different methods to estimate DSM uncertainty and show that this has a large impact on centimeter-level topographical change detection. The DSM reconstruction and surface change detection based on a DSLR and action camera were reproducible: the main difference lies in the level of detail of the surface representations. The PPK–SfM workflow in the context of 4-D Earth surface monitoring should be considered an efficient tool to monitor geomorphic processes accurately and quickly at a very high spatial and temporal resolution.

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Analysis of Application of Cluster Descriptions in Space of Characteristic Image Features

Data ◽

10.3390/data3040052 ◽

2018 ◽

Vol 3 (4) ◽

pp. 52 ◽

Cited By ~ 2

Author(s):

Oleksii Gorokhovatskyi ◽

Volodymyr Gorokhovatskyi ◽

Olena Peredrii

Keyword(s):

Recognition Performance ◽

Input Image ◽

Image Features ◽

Additional Time ◽

Scale Invariant ◽

Speeded Up Robust Features ◽

Image Descriptors ◽

Structural Image ◽

Characteristic Features ◽

Scale Invariant Feature

In this paper, we propose an investigation of the properties of structural image recognition methods in the cluster space of characteristic features. Recognition, which is based on key point descriptors like SIFT (Scale-invariant Feature Transform), SURF (Speeded Up Robust Features), ORB (Oriented FAST and Rotated BRIEF), etc., often relating to the search for corresponding descriptor values between an input image and all etalon images, which require many operations and time. Recognition of the previously quantized (clustered) sets of descriptor features is described. Clustering is performed across the complete set of etalon image descriptors and followed by screening, which allows for representation of each etalon image in vector form as a distribution of clusters. Due to such representations, the number of computation and comparison procedures, which are the core of the recognition process, might be reduced tens of times. Respectively, the preprocessing stage takes additional time for clustering. The implementation of the proposed approach was tested on the Leeds Butterfly dataset. The dependence of cluster amount on recognition performance and processing time was investigated. It was proven that recognition may be performed up to nine times faster with only a moderate decrease in quality recognition compared to searching for correspondences between all existing descriptors in etalon images and input one without quantization.

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A novel method for harmonic geometric transformation model based on wavelet collocation

Object recognition supported by user interaction for service robots ◽

10.1109/icpr.2002.1044586 ◽

2003 ◽

Cited By ~ 1

Author(s):

Y.Y. Tang ◽

X.C. Feng ◽

Xinge You ◽

Z.W. Liao ◽

L. Sun

Keyword(s):

Transformation Model ◽

Geometric Transformation ◽

Model Based ◽

Novel Method

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UAV AND LIDAR IMAGE REGISTRATION: A SURF-BASED APPROACH FOR GROUND CONTROL POINTS SELECTION

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-2-w13-413-2019 ◽

2019 ◽

Vol XLII-2/W13 ◽

pp. 413-418 ◽

Cited By ~ 1

Author(s):

B. Kalantar ◽

N. Ueda ◽

H. A. H. Al-Najjar ◽

H. Moayedi ◽

A. A. Halin ◽

...

Keyword(s):

Image Registration ◽

Water Resource Management ◽

Feature Matching ◽

Image Data ◽

Ground Control ◽

Control Points ◽

Speeded Up Robust Features ◽

Ground Control Points ◽

Edge Detectors ◽

Edge Features

<p><strong>Abstract.</strong> Multisource remote sensing image data provides synthesized information to support many applications including land cover mapping, urban planning, water resource management, and GIS modelling. Effectively utilizing such images however requires proper image registration, which in turn highly relies on accurate ground control points (GCP) selection. This study evaluates the performance of the interest point descriptor SURF (Speeded-Up Robust Features) for GCPs selection from UAV and LiDAR images. The main motivation for using SURF is due to it being invariant to scaling, blur and illumination, and partially invariant to rotation and view point changes. We also consider features generated by the Sobel and Canny edge detectors as complements to potentially increase the accuracy of feature matching between the UAV and LiDAR images. From our experiments, the red channel (Band-3) produces the most accurate and practical results in terms of registration, while adding the edge features seems to produce lacklustre results.</p>

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Obtaining High-Resolution Seabed Topography and Surface Details by Co-Registration of Side-Scan Sonar and Multibeam Echo Sounder Images

Remote Sensing ◽

10.3390/rs11121496 ◽

2019 ◽

Vol 11 (12) ◽

pp. 1496 ◽

Cited By ~ 9

Author(s):

Shang ◽

Zhao ◽

Zhang

Keyword(s):

High Resolution ◽

Template Matching ◽

High Accuracy ◽

Transformation Model ◽

Base Line ◽

Initial Image ◽

Side Scan Sonar ◽

Speeded Up Robust Features ◽

Seabed Topography ◽

Echo Sounder

Side-scan sonar (SSS) is used for obtaining high-resolution seabed images, but with low position accuracy without using the Ultra Short Base Line (USBL) or Short Base Line (SBL). Multibeam echo sounder (MBES), which can simultaneously obtain high-accuracy seabed topography as well as seabed images with low resolution in deep water. Based on the complementarity of SSS and MBES data, this paper proposes a new method for acquiring high-resolution seabed topography and surface details that are difficult to obtain using MBES or SSS alone. Firstly, according to the common seabed features presented in both images, the Speeded-Up Robust Features (SURF) algorithm, with the constraint of image geographic coordinates, is adopted for initial image matching. Secondly, to further improve the matching performance, a template matching strategy using the dense local self-similarity (DLSS) descriptor is adopted according to the self-similarities within these two images. Next, the random sample consensus (RANSAC) algorithm is used for removing the mismatches and the SSS backscatter image geographic coordinates are rectified by the transformation model established based on the correct matched points. Finally, the superimposition of this rectified SSS backscatter image on MBES seabed topography is performed and the high-resolution and high-accuracy seabed topography and surface details can be obtained.

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Improving the Positional Accuracy of Digital Cadastral Maps through Optimal Geometric Transformation

Journal of Surveying Engineering ◽

10.1061/(asce)su.1943-5428.0000217 ◽

2017 ◽

Vol 143 (3) ◽

pp. 05017002 ◽

Cited By ~ 2

Author(s):

Nedim Tuno ◽

Admir Mulahusić ◽

Dušan Kogoj

Keyword(s):

Geometric Transformation ◽

Positional Accuracy ◽

Cadastral Maps

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Evaluating the Potential of PPK Direct Georeferencing for UAV-SfM Photogrammetry and Precise Topographic Mapping

10.5194/esurf-2019-2 ◽

2019 ◽

Cited By ~ 1

Author(s):

He Zhang ◽

Emilien Aldana-Jague ◽

François Clapuyt ◽

Florian Wilken ◽

Veerle Vanacker ◽

...

Keyword(s):

Focal Length ◽

Positional Accuracy ◽

Ground Control Points ◽

Time Period ◽

Surface Models ◽

Flight Height ◽

Aerial Vehicle ◽

Repeatability And Reproducibility ◽

Uav Images ◽

Topography Data

Abstract. Images captured by Unmanned aerial vehicle (UAV) and processed by Structure from Motion (SfM) photogrammetry are increasingly used in geomorphology to obtain high resolution topography data. Conventional georeferencing using ground control points (GCPs) provides reliable positioning but the geometrical accuracy critically depends on the number and spatial layout of the GCPs. This limits the time- and cost-effectiveness. Direct georeferencing of the UAV images with differential GNSS, such as PPK (Post-Processing Kinematic), may overcome these limitations by providing accurate and directly georeferenced surveys. To investigate the positional accuracy, repeatability and reproducibility of digital surface models (DSMs) generated by a UAV-PPK-SfM workflow, we carried out multiple flight missions with different camera/UAV systems. Our analysis showed that the PPK solution provides the same accuracy (mean: ca. 0.01 m, RMSE: ca. 0.03 m) as the GCP method. Furthermore, our results indicated that camera properties (i.e., focal length, resolution, sensor quality) have an impact on the accuracy but planimetric and altimetric errors remained in the range of 0.011 to 0.024 m. By analysing the repeatability of DSM construction over a time period of a few months, our study demonstrates that a UAV-PPK-SfM workflow can provide consistent, repeatable 4D data with an accuracy of a few centimetres without the use of GCPs. An uncertainty analysis showed that the minimum level of topographical change detection was ca. ±0.04 m for a high-end DSLR camera and ca. ±0.08 m for an action camera (for a flight height of 45 m). The level of detection substantially improved when reducing the UAV flight height. This study demonstrates the repeatability, reproducibility and efficiency of a PPK-SfM workflow in the context of 4D earth surface monitoring with time-laps SfM photogrammetry. As such, it should be considered as an efficient tool to monitor geomorphic processes accurately and quickly at a very high spatial and temporal resolution.

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