scholarly journals INFLUENCE OF RAW IMAGE PREPROCESSING AND OTHER SELECTED PROCESSES ON ACCURACY OF CLOSE-RANGE PHOTOGRAMMETRIC SYSTEMS ACCORDING TO VDI 2634

2016 ◽  
Vol XLI-B5 ◽  
pp. 107-113 ◽  
Author(s):  
J. Reznicek ◽  
T. Luhmann ◽  
C. Jepping
Keyword(s):  
Lens Distortion ◽  
Test Field ◽  
Image Preprocessing ◽  
Multi Scale ◽  
Estimated Parameters ◽  
Close Range ◽  
Validation Procedure ◽  
Measuring Lines ◽  
Target Detecting ◽  
Photogrammetric Measurement

This paper examines the influence of raw image preprocessing and other selected processes on the accuracy of close-range photogrammetric measurement. The examined processes and features includes: raw image preprocessing, sensor unflatness, distance-dependent lens distortion, extending the input observations (image measurements) by incorporating all RGB colour channels, ellipse centre eccentricity and target detecting. The examination of each effect is carried out experimentally by performing the validation procedure proposed in the German VDI guideline 2634/1. The validation procedure is based on performing standard photogrammetric measurements of high-accurate calibrated measuring lines (multi-scale bars) with known lengths (typical uncertainty = 5 μm at 2 sigma). The comparison of the measured lengths with the known values gives the maximum length measurement error LME, which characterize the accuracy of the validated photogrammetric system. For higher reliability the VDI test field was photographed ten times independently with the same configuration and camera settings. The images were acquired with the metric ALPA 12WA camera. The tests are performed on all ten measurements which gives the possibility to measure the repeatability of the estimated parameters as well. The influences are examined by comparing the quality characteristics of the reference and tested settings.

scholarly journals INFLUENCE OF RAW IMAGE PREPROCESSING AND OTHER SELECTED PROCESSES ON ACCURACY OF CLOSE-RANGE PHOTOGRAMMETRIC SYSTEMS ACCORDING TO VDI 2634

2016 ◽  
Vol XLI-B5 ◽  
pp. 107-113 ◽  
Author(s):  
J. Reznicek ◽  
T. Luhmann ◽  
C. Jepping
Keyword(s):  
Lens Distortion ◽  
Test Field ◽  
Image Preprocessing ◽  
Multi Scale ◽  
Estimated Parameters ◽  
Close Range ◽  
Validation Procedure ◽  
Measuring Lines ◽  
Target Detecting ◽  
Photogrammetric Measurement

This paper examines the influence of raw image preprocessing and other selected processes on the accuracy of close-range photogrammetric measurement. The examined processes and features includes: raw image preprocessing, sensor unflatness, distance-dependent lens distortion, extending the input observations (image measurements) by incorporating all RGB colour channels, ellipse centre eccentricity and target detecting. The examination of each effect is carried out experimentally by performing the validation procedure proposed in the German VDI guideline 2634/1. The validation procedure is based on performing standard photogrammetric measurements of high-accurate calibrated measuring lines (multi-scale bars) with known lengths (typical uncertainty = 5 μm at 2 sigma). The comparison of the measured lengths with the known values gives the maximum length measurement error LME, which characterize the accuracy of the validated photogrammetric system. For higher reliability the VDI test field was photographed ten times independently with the same configuration and camera settings. The images were acquired with the metric ALPA 12WA camera. The tests are performed on all ten measurements which gives the possibility to measure the repeatability of the estimated parameters as well. The influences are examined by comparing the quality characteristics of the reference and tested settings.

scholarly journals DoF-Dependent and Equal-Partition Based Lens Distortion Modeling and Calibration Method for Close-Range Photogrammetry

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5934
Author(s):  
Xiao Li ◽  
Wei Li ◽  
Xin’an Yuan ◽  
Xiaokang Yin ◽  
Xin Ma
Keyword(s):  
Optical Axis ◽  
Focal Length ◽  
Calibration Method ◽  
Depth Of Field ◽  
Model Parameters ◽  
Lens Distortion ◽  
Camera Model ◽  
Distortion Model ◽  
Manual Adjustment ◽  
Close Range

Lens distortion is closely related to the spatial position of depth of field (DoF), especially in close-range photography. The accurate characterization and precise calibration of DoF-dependent distortion are very important to improve the accuracy of close-range vision measurements. In this paper, to meet the need of short-distance and small-focal-length photography, a DoF-dependent and equal-partition based lens distortion modeling and calibration method is proposed. Firstly, considering the direction along the optical axis, a DoF-dependent yet focusing-state-independent distortion model is proposed. By this method, manual adjustment of the focus and zoom rings is avoided, thus eliminating human errors. Secondly, considering the direction perpendicular to the optical axis, to solve the problem of insufficient distortion representations caused by using only one set of coefficients, a 2D-to-3D equal-increment partitioning method for lens distortion is proposed. Accurate characterization of DoF-dependent distortion is thus realized by fusing the distortion partitioning method and the DoF distortion model. Lastly, a calibration control field is designed. After extracting line segments within a partition, the de-coupling calibration of distortion parameters and other camera model parameters is realized. Experiment results shows that the maximum/average projection and angular reconstruction errors of equal-increment partition based DoF distortion model are 0.11 pixels/0.05 pixels and 0.013°/0.011°, respectively. This demonstrates the validity of the lens distortion model and calibration method proposed in this paper.

The Application of Close-Range Digital Photogrammetry Based on the Neural Network in Crack-Monitoring

2011 ◽  
Vol 90-93 ◽  
pp. 2875-2880
Author(s):  
Ming Ming Li ◽  
Jian Gong Chen ◽  
Yong Xing Zhang
Keyword(s):  
Neural Network ◽  
New Technology ◽  
Lens Distortion ◽  
Two Dimensional ◽  
Digital Photogrammetry ◽  
The Neural Network ◽  
Crack Monitoring ◽  
Close Range ◽  
Grid Points ◽  
Linear Neural Network

Based on the two-dimensional Direct Linear Transformation (DLT) principle of close-range digital photogrammetry and mathematical principle of the linear neuron, the equivalent relationship between linear neural network and the two-dimensional DLT of close-range digital photogrammetry is discussed. A neural network with 2 linear neurons, 6 input parameters and 2 output parameters is established to simulate the two-dimensional DLT. The network can be trained using a set of grid points in the control coordinate system with known world coordinates and pixel coordinates. The weights and biases of trained network contain camera interior and exterior parameters. A new digital photographic technique is put forward combined camera self-calibration based on neural network with non-linear pixel coordinates correction of lens distortion. The indoor survey test indicates that measurement is more accuracy. Meanwhile, the new technology is successfully used in crack monitor of a bridge pier.

scholarly journals Analysis and Evaluation of the Image Preprocessing Process of a Six-Band Multispectral Camera Mounted on an Unmanned Aerial Vehicle for Winter Wheat Monitoring

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 747 ◽  
Author(s):  
Jiale Jiang ◽  
Hengbiao Zheng ◽  
Xusheng Ji ◽  
Tao Cheng ◽  
Yongchao Tian ◽  
...  
Keyword(s):  
Quality Data ◽  
Leaf Biomass ◽  
Lens Distortion ◽  
High Quality ◽  
Radiometric Correction ◽  
High Quality Data ◽  
Image Preprocessing ◽  
Crop Monitoring ◽  
Aerial Vehicle ◽  
Multispectral Sensors

Unmanned aerial vehicle (UAV)-based multispectral sensors have great potential in crop monitoring due to their high flexibility, high spatial resolution, and ease of operation. Image preprocessing, however, is a prerequisite to make full use of the acquired high-quality data in practical applications. Most crop monitoring studies have focused on specific procedures or applications, and there has been little attempt to examine the accuracy of the data preprocessing steps. This study focuses on the preprocessing process of a six-band multispectral camera (Mini-MCA6) mounted on UAVs. First, we have quantified and analyzed the components of sensor error, including noise, vignetting, and lens distortion. Next, different methods of spectral band registration and radiometric correction were evaluated. Then, an appropriate image preprocessing process was proposed. Finally, the applicability and potential for crop monitoring were assessed in terms of accuracy by measurement of the leaf area index (LAI) and the leaf biomass inversion under variable growth conditions during five critical growth stages of winter wheat. The results show that noise and vignetting could be effectively removed via use of correction coefficients in image processing. The widely used Brown model was suitable for lens distortion correction of a Mini-MCA6. Band registration based on ground control points (GCPs) (Root-Mean-Square Error, RMSE = 1.02 pixels) was superior to that using PixelWrench2 (PW2) software (RMSE = 1.82 pixels). For radiometric correction, the accuracy of the empirical linear correction (ELC) method was significantly higher than that of light intensity sensor correction (ILSC) method. The multispectral images that were processed using optimal correction methods were demonstrated to be reliable for estimating LAI and leaf biomass. This study provides a feasible and semi-automatic image preprocessing process for a UAV-based Mini-MCA6, which also serves as a reference for other array-type multispectral sensors. Moreover, the high-quality data generated in this study may stimulate increased interest in remote high-efficiency monitoring of crop growth status.

Use of Laser Scanner for Digital Surveying of the Sarnicli Inn and the Byzantine Cistern Underneath

2017 ◽  
pp. 227-254
Author(s):  
Gülhan Benli ◽  
Eylem Görmüş Ekizce
Keyword(s):  
Cultural Heritage ◽  
Protected Areas ◽  
Laser Scanning ◽  
Laser Scanner ◽  
3D Scanning ◽  
Measurement Methods ◽  
Advanced Technology ◽  
Laser Scanners ◽  
Close Range ◽  
Photogrammetric Measurement

Measurement methods including traditional measurement methods, topographic and photogrammetric measurement methods, measurements via laser scanning devices and aerial photogrammetric measurement methods obtained using model airplane or model helicopters are used in documentation of the cultural heritage and protected areas in our country. Although data obtained by Aerial Lidar technology accepted as advanced technology over the past decade, enables faster data comparing to others as data obtained by terrestrial laser scanners provide millimetre level accuracy close-range scanning methods are preferred in architectural facades scanning during the process of surveying of a single building. Inclusion process of a Byzantine cistern in Istanbul, Turkey, which was undiscovered for centuries, in our cultural heritage as well as surveying stages of the cistern along with the inn structure built over, using 3D scanning technology shall be described within this study.

scholarly journals The New Approach to Camera Calibration – GCPs or TLS Data?

2016 ◽  
Vol XLI-B3 ◽  
pp. 75-82
Author(s):  
J. Markiewicz ◽  
P. Podlasiak ◽  
M. Kowalczyk ◽  
D. Zawieska
Keyword(s):  
Camera Calibration ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Automatic Identification ◽  
Test Field ◽  
Control Points ◽  
Data Set ◽  
Laser Measurements ◽  
Close Range ◽  
Processed Products

Camera calibration is one of the basic photogrammetric tasks responsible for the quality of processed products. The majority of calibration is performed with a specially designed test field or during the self-calibration process. The research presented in this paper aims to answer the question of whether it is necessary to use control points designed in the standard way for determination of camera interior orientation parameters. Data from close-range laser scanning can be used as an alternative. The experiments shown in this work demonstrate the potential of laser measurements, since the number of points that may be involved in the calculation is much larger than that of commonly used ground control points. The problem which still exists is the correct and automatic identification of object details in the image, taken with a tested camera, as well as in the data set registered with the laser scanner.

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