Image Point Coordinates Research Articles

Methods of mapping the lands disturbed by mining operations and accuracy of cartographic images obtained from Unmanned Aerial Vehicles: A review

Purpose. Analyzing the land disturbance consequences caused by surface mining operations and methods for mapping these lands, as well as studying the accuracy of point coordinates of digital images obtained from materials of aerial photographic surveys using Unmanned Aerial Vehicles (UAVs). Performing a quantitative assessment of the Root Mean Square Error (RMSE) of point coordinates on cartographic images and determining the dependences of the RMSE of point coordinates on the photogrammetric parameters. Methods. The review of previous research publications within the framework of the presented subject is performed in the following sequence: analysis of ecosystem disbalance as a result of surface mining operations; based on previous studies, collecting the data for quantitative assessment of accuracy in the form of RMSE of point coordinates on cartographic images obtained from the materials of aerial photographic survey using UAVs; statistical study of the relationship between the RMSE and photographic survey parameters. Findings. The methods for mapping the disturbed lands to return them to their natural state after the consequences of surface mining operations are presented, based on a review of previous research publications on the subject of the work. According to the previous studies, the RMSE of point coordinates of cartographic images has been systematized, and, based on this, the accuracy of topographic plans has been determined for them. Statistical studies of the relationship between the quantitative assessment of the RMSE (xy) and RMSE (z) accuracy in relation to the photographic survey parameters have been performed. In addition, the scattering diagrams of the correlation dependence and the range of RMSE relative frequency have been presented. Originality. Based on a critical analysis of previous studies on the lack of quantitative accuracy regulation of cartographic images obtained from aerial photographic survey using UAVs, the RMSE systematics has been performed in terms of the photographic survey height. Based on this, the accuracy of topographic plans, the relative frequency of horizontal and vertical distribution of errors, the mean value and the root mean square error (σ) have been determined. Practical implications. The systematics of the RMSE values of cartographic image point coordinates for certain photographic survey parameters and the scale of topographic images makes it possible to take this into account in the project of aerial photographic survey using UAVs of lands for various purposes, as well as to choose the height and photographic equipment according to the required accuracy.

Model and compensation method of image point drift caused by self-heating of industrial camera

In order to reduce the influence of temperature on the image point coordinates of industrial cameras in visual measurement, the image point drift caused by the self-heating of the camera was studied, and a compensation method for the thermal image point drift of industrial cameras was proposed. The finite element simulation analysis of the industrial camera model through Ansys Workbench shows that the self-heating of the industrial camera will cause the imaging optical path change and sensor expansion change, quantitatively the influence of the optical path change and sensor expansion on the image point coordinates was analyzed, and the image point drift compensation model was established. A large number of experiments have shown that the image point drift error compensated by the model is reduced from 0.4-0.6 pixel to 0.1-0.2 pixel, which is equivalent to the image point drift suppression effect achieved by hardware thermal control. However, compared with the thermal control device, the method of using the model for compensation has obvious advantages of simple structure and low cost. The temperature compensation model proposed in this research provides a theoretical basis for reducing the image point drift error caused by the self-heating of the camera in the visual measurement.

SVD-clustering, a general image-analyzing method explained and demonstrated on model and Raman micro-spectroscopic maps

An image analyzing method (SVD-clustering) is presented. Amplitude vectors of SVD factorization (V1…Vi) were introduced into the imaging of the distribution of the corresponding Ui basis-spectra. Since each Vi vector contains each point of the map, plotting them along the X, Y, Z dimensions of the map reconstructs the spatial distribution of the corresponding Ui basis-spectrum. This gives valuable information about the first, second, etc. higher-order deviations present in the map. We extended SVD with a clustering method, using the significant Vi vectors from the VT matrix as coordinates of image points in a ne-dimensional space (ne is the effective rank of the data matrix). This way every image point had a corresponding coordinate in the ne-dimensional space and formed a point set. Clustering was applied to this point set. SVD-clustering is universal; it is applicable to any measurement where data are recorded as a function of an external parameter (time, space, temperature, concentration, species, etc.). Consequently, our method is not restricted to spectral imaging, it can find application in many different 2D and 3D image analyses. Using SVD-clustering, we have shown on models the theoretical possibilities and limitations of the method, especially in the context of creating, meaning/interpreting of cluster spectra. Then for real-world samples, two examples are presented, where we were able to reveal minute alterations in the samples (changing cation ratios in minerals, differently structured cellulose domains in plant root) with spatial resolution.

A fast and accurate iterative method for the camera pose estimation problem

This paper presents a fast and accurate iterative method for camera pose estimation problem. The dependence on initial values is reduced by replacing unknown angular parameters with three independent non-angular parameters. Image point coordinates are treated as observations with errors and a new model is built using a conditional adjustment with parameters for relative orientation. This model allows for the estimation of the errors in the observations. The estimated observation errors are then used iteratively to detect and eliminate gross errors in the adjustment. A total of 22 synthetic datasets and 10 real datasets are used to compare the proposed method with the traditional iterative method, the 5-point-RANSAC and the state-of-the-art 5-point-USAC methods. Preliminary results show that our proposed method is not only faster than the other methods, but also more accurate and stable.

Block Adjustment for Satellite Imagery Based on the Strip Constraint

Given that long strip satellite images have the same error distribution characteristics, we propose a block adjustment method for satellite images based on the strip constraint. First, the image point coordinates are calculated in the strip image coordinate system based on the offset value of the adjacent image. Second, the rational function model (RFM) of the strip image is regenerated using the RFM of single images, and the compensation grid is also generated. Third, block adjustment of the strip image is implemented based on the RFM with an affine transformation parameter. Finally, the affine transformation parameters of single images are recalculated using the affine transformation parameters of the strip image. Experiments using ZY-3 satellite images showed that block adjustment of satellite images based on a strip constraint (strip adjustment) can produce better results than block adjustment of satellite images based on a single image in sparse control conditions. The test results demonstrated the effectiveness and feasibility of the proposed method.

Projector Calibration Method using Orthogonal Gray Code Combined with Trapezoid Phase Shift Code

In coded-structured light three dimensional measurement system, system calibration plays an important role for the measurement accuracy. Projector calibration is an important part of the system calibration. Therefore, this paper proposes a projector calibration method with simple calibration process and high accuracy. This method combines Zhang’s plane model calibration method with orthogonal Gray code + trapezoid phase shift code. During the calibration process, this paper uses Gray code pattern and trapezoid phase shift code pattern to establish the relation of projector image and camera point coordinates, the corner extraction accuracy of this paper’s method is higher than the traditional orthogonal Gray code. According to the image coordinates in the projector’s perspective, we program and calculate the projector’s internal and external parameters matrix based on the Zhang’s plane model calibration toolbox. The results show that this paper’s method is simple and flexible, the maximum relative error of the calibration parameters is 0.027%, and it meets the requirements of system calibration in engineering or industrial fields.

Coded-Structured Light System Calibration Using Orthogonal Phase Shift Coding Combined with Zhang’s Method

In coded-structured light three dimensional system, system calibration plays a vital role for the measurement accuracy. The camera calibration method is very mature, but the study about projector calibration is less. Therefore, this paper proposes a projector calibration method with simple calibration process and high accuracy. This method combines the Zhang’?s plane model calibration method with orthogonal phase shift coding. In calibration process, this paper uses phase shift coding pattern to establish the relationship of projector image and camera corner point coordinates. According to the image coordinates in the projector’?s perspective, we program and calculate the projector’?s internal and external parameters matrix based on the Zhang’?s plane model calibration toolbox. The results show that the proposed method is simple and flexible, the maximum relative error of the calibration parameters is 0.03%, and it meets the requirements of system calibration in medical or industrial fields.

Calibration of Smooth Camera Models

Generic imaging models can be used to represent any camera. Current generic models are discrete and define a mapping between each pixel in the image and a straight line in 3D space. This paper presents a modification of the generic camera model that allows the simplification of the calibration procedure. The only requirement is that the coordinates of the 3D projecting lines are related by functions that vary smoothly across space. Such a model is obtained by modifying the general imaging model using radial basis functions (RBFs) to interpolate image coordinates and 3D lines, thereby allowing both an increase in resolution (due to their continuous nature) and a more compact representation. Using this variation of the general imaging model, we also develop a calibration procedure. This procedure only requires that a 3D point be matched to each pixel. In addition, not all the pixels need to be calibrated. As a result, the complexity of the procedure is significantly decreased. Normalization is applied to the coordinates of both image and 3D points, which increases the accuracy of the calibration. Results with both synthetic and real datasets show that the model and calibration procedure are easily applicable and provide accurate calibration results.

Network Orientation Using the Scaled Orthographic Projection for Parameter Initialization

Bundle adjustment is a well known and reliable method used in photogrammetry for image network orientation which requires relatively accurate initial approximations of image orientations and point coordinates. The initialization problem has proved difficult and a variety of initialization techniques have been proposed. We present a new method that takes advantage of the scaled orthographic projection to compute direct linear solutions that approximate the image network geometry. The algorithm includes two relative orientation methods adapted from previous work, and incorporates a recently developed orthographic bundle adjustment method. Following initial network orientation, image coordinates are corrected for perspective to obtain an intermediate solution which is converted into perspective projection parameters and a final bundle adjustment is performed. The method has been tested using several image sets and has proven to be effective at various fields of view, with a variety of imaging network geometries, and with different object point geometries.

Quadric surface projection model for fish-eye cameras

The curved surface projection model in fisheye image correction algorithm is presented. To analyze the causes of distortion in existing models, we establish an ideal surface projection model and compare its surface with the surfaces of existing models. Subsequently, feature points are obtained on the ideal surface according to the relationship of coordinates of fish-eye image points and their ideal three-dimentional (3D) points. Finally, the least square method is used to obtain a quadric surface and presents a quadric surface projection model. The experiment shows that the corrected image of the new model is more similar to the actual scene than the corrected images of previous models.

A Fast Approach to Best Scanline Search of Airborne Linear Pushbroom Images

The linear pushbroom camera has become one of the most important imaging sensors in today's photogrammetry and remote sensing practices. Airborne digital sensors (ADS) or three-line scanner (TLS) imaging system such as the ADS40 from Leica Geosystems and STARIMAGER from STAR-LABO Corporation use the pushbroom technique to collect high-resolution, multi-channel seamless image strips. As we know, the object-to-image coordinate computation serves as a core step during the process of photogrammetric images. However, each scanline captured by a linear pushbroom sensor has six exterior orientation ( E O) parameters at the corresponding instant of exposure. The image point coordinates will not be accurately calculated through colinearity equations unless reasonable EO parameters are determined. Therefore, the best scanline search (BSS) has direct effects on efficiency of object-to-image coordinate computation during image processing. This paper addresses a fast BSS method based on the novel central perspective plane of scanline (CPPS) constraints. The search process is simply performed through analytical geometric calculations, which can significantly improve the efficiency of the object-to-image coordinate computation. The feasibility and robustness of the proposed method have been verified using ADS40 and STARIMAGER images. Experimental results show that the proposed method improves scanline search speed considerably with the time cost decreased by nearly 85 percent compared with the traditional methods.

Migration/inversion: think image point coordinates, process in acquisition surface coordinates

We state a general principle for seismic migration/inversion processes: think image point coordinates; compute in surface coordinates. This principle allows the natural separation of multiple travel paths of energy from a source to a reflector to a receiver. Further, the Beylkin determinant (Jacobian of transformation between processing parameters and acquisition surface coordinates) is particularly simple in stark contrast to the common-offset Beylkin determinant in standard single arrival Kirchhoff .A feature of this type of processing is that it changes the deconvolution structure of Kirchhoff operators or the deconvolution imaging operator of wave equation migration into convolution operators; that is, division by Green's functions is replaced by multiplications by adjoint Green's functions.This transformation from image point coordinates to surface coordinates is also applied to a recently developed extension of the standard Kirchhoff inversion method. The standard method uses Green's functions in the integration process and tends to produce more imaging artefacts than alternatives, such as methods using Gaussian beam representations of Green's functions in the inversion formula. These methods point to the need for a true-amplitude Kirchhoff technique that uses more general Green's functions: Gaussian beams, true-amplitude one-way Green's functions, or Green's functions from the two-way wave equation. Here, we present a derivation of a true-amplitude Kirchhoff that uses these more general Green's functions. When this inversion is recast as an integral over all sources and receivers, the formula is surprisingly simple.

Computing rigorous bounds to the accuracy of calibrated stereo reconstruction

The authors deal with the problem of computing rigorous bounds on the position of 3-D points obtained by stereo triangulation when both the camera matrix and the coordinates of image points are affected by measurement errors. By ‘rigorous bounds’ it is meant that the true unknown 3-D points are guaranteed to lie within the intervals computed by the method, with mathematical certainty. To this end, the calibration process is first modelled by assuming a bounded error in the localisation of the reference points in the image, then narrow intervals are computed for the entries of the camera matrix using numerical methods based on interval analysis. Finally, triangulation is applied to obtain cuboids that bound point coordinates. Two state-of-the-art methods were employed for the solution of linear systems of interval equations, namely Rump's and Shary's methods. It is concluded that a careful selection of numerical techniques allows the use of interval analysis as a tool for obtaining realistic bounds on the output error, even in the presence of significant errors in the input data.

Trifocal tensors for weak perspective and paraperspective projections

Trilinear relationships among the image point coordinates obtained by perspective projection of several feature points over three views have been investigated, and it has been shown that seven point correspondences are sufficient to determine the coefficients involved. We show that analogous trilinear relationships exist for the weak perspective and paraperspective projections, and that only four point correspondences are necessary for the determination of the coefficients. When the trilinear relationships are known, the position of the image of a point in one camera system can be determined from its image in the two other camera systems through linear equations.

3-D localization of cardiac structures in real time

Radiographic 3-D localisation enables measurements to be made that facilitate the placement of the interventional device during cardiac intervention. To enable the reader to implement the method himself, we describe the computation of 3-D coordinates, acquisition of the imaging and projection data on-line, and the accuracy that can be expected with the method. The 3-D coordinates of a cardiac structure are calculated from the image point coordinates, the projection data and the system constants of a biplane isocentric X-ray unit. Technical imaging errors are corrected a priori. The biplane projection data of a run are acquired on-line and stored in a data base. The image pair of interest is identified automatically from the inscribed run number, and assigned to the projection data from the data base. The target image point is marked on the monitor for 3-D localisation. The accuracy of the method was determined by comparing the calculated and actual cross-sectional points of a centimetre grid imaged in biplane X-ray projections. 3-D localisation took an average of 9.8 +/- 1.2 seconds. Angles and distances were assessed with a standard error of 1.1 degrees and 0.8 mm. The run number is identified correctly in 98.5% of the cases. The mean absolute location error for all points and image pairs was 0.61 +/- 0.32 mm. The accuracy and precision was 0.03 +/- 0.40 mm. Radiographic 3-D localisation can be performed readily and accurately on-line. The results obtained with the method enable interventional decisions to be optimized.

The use of non-metric cameras in short-range photogrammetry

This paper deals with the use of non-metric cameras in short-range stereophotogrammetry with particular reference to a pair of MAMIYA C330 Professional Cameras. The distortion characteristics of the lenses are studied and the camera system is tested when resulting photography is used in a stereophotogrammetric analytical and analogue (stereoplotting) mode. The advantage of using projective transformation theory in short-range stereophotogrammetry is discussed and the potential accuracy of using a digitiser as a monocomparator to measure X-Y coordinates of image points on positive print enlargements of stereophotographs is demonstrated.