Interior Orientation Elements Research Articles

Применение сферической модели камеры для решения фотограмметрических задач

In this paper, we consider the Unified Camera Model and its properties, as well as investigate and apply the improved Double-Spherical one (DS-model) in the task of restoring exterior and interior orientation elements for a set of images with ultra-wide-angle fisheye lens. The use of panoramic cameras in photogrammetry issues is a new trend, while the spherical model fully inherits the properties of the classical central-projection sample. The mathematical concept of using it is presented, as well as the solution of the optimization problem of calculating the elements of the internal and external orientation of the camera through the Gauss-Newton method, which is relevant for the tasks of reconstructing a three-dimensional scene and developing an optical SLAM based on a multi-camera system with ultra-wide-angle lenses, is implemented. In this work, epipolar geometry methods, digital image processing methods, statistical, numerical, and optimization ones were used. The results obtained enable evaluating the applicability of the DS-model for three-dimensional reconstruction of scenes during external and internal monitoring of buildings and structures, restoration of the motion trajectory and position in space for mobile systems with an installed camera, solving matters such as Perspective-n-Point for restoring the relative orientation between different active and passive sensors

Optical design and precision analysis of a single-line-array pendulum sweep high-resolution mapping camera.

With the improvement of the satellite resolution, it is urgent to develop the single-line-array mapping camera. However, the camera accuracy is influenced by the satellite attitude's rapid maneuvering during the imaging process. In our study, a coaxial four-mirror optical system with a field bias with a focal length of 7050mm, F-number of 10.8, field of view of 1.2°, and spectral range of 450-800nm is designed. By combining mathematical modeling and ray tracing, the offset of the camera interior orientation elements caused by the misalignment of the secondary mirror is derived. The simulation results show that the maximum relative error does not exceed 2.119%. Besides, a desensitization design method based on the magnification parameter control method is proposed, and the results show that the sensitivity of camera interior orientation elements to the secondary mirror is reduced, indicating the effectiveness of the system desensitization design, which is of great significance for the improvement of camera accuracy.

ПРОВЕДЕНИЕ КАЛИБРОВКИ НЕМЕТРИЧЕСКОЙ ФОТОКАМЕРЫ В БЕСПИЛОТНОМ ЛЕТАТЕЛЬНОМ АППАРАТЕ ПРИ МОНИТОРИНГЕ ЗЕМЕЛЬ

Recently, unmanned aerial vehicles (UAVs) have been widely used in our country and in the world. This is due to continuity, endurance, the ability to work under overload conditions and the exclusion of the human factor. In recent years, there has been a revolutionary leap in the development of UAVs, which made it possible to divide this market segment into completely different price categories. The increase in the use of UAVs has made this product really in demand and was able to introduce it into various areas of life. This also applies to geodetic measurements. Photogrammetry methods began to work closely with methods of easy-to-control unmanned aerial vehicles. But at the same time, the demand for filming equipment is growing, the pricing policy of which sometimes considerably exceeds the cost of the aircraft itself, which complicates photogrammetric work. This aspect has led to research on the possibility of using inexpensive non-professional cameras on UAVs for photogrammetry, due to obtaining accurate measurements. For such cameras, there is such a thing as calibration, which includes the definition of interior orientation elements. This article discusses the use of non-metric cameras on UAVs in order to reduce the cost of work to monitor agricultural land. The following materials were used as initial data in this work: test images from the UAV at the test site; software such as SAS.Planet, MatLAb, MdCockpit V2.6.2.6, PHOTOMOD. To perform this work, the following equipment was used: unmanned aerial vehicle; non-metric digital camera. To calibrate the camera, the terrain was surveyed using Zala 421-21.

Topographic Surveying using Low-Cost Amateur Drones & 4K Ultra-High-Definition Videos

These days, the science of photogrammetry is frequently used in a wide range of applications, including engineering geology, medication, security, navigation, and topographic surveying works. Drones have gradually become an effectual and frequent technique for obtaining a number of photogrammetric products, such as ortho-mosaics, Digital Elevation Model (DEM), and land detailed topographic maps. This paper investigates the possibility of employing low-cost amateur drones with 4K Ultra-High-Definition (UHD) video for topographic surveying works and creating DEM's. DJI Mavic 2 PRO drone with Hasselblad L1D-20C 20 MP camera has been used for covering an expected gas & oil pipeline route in the South of Libya with length of nearly 15 km and width of 200 m. 60 well-distributed high-quality 3D ground points, divided as 30 Ground Control Points (GCP's) and 30 check points, have been used for more stable and robust photogrammetric processing and for reliable evaluation, respectively. The camera has been calibrated twice, before and after executing the flight mission for trustworthy Interior Orientation Elements (IOE's). The recorded video has been split into smaller videos based on the capturing time of the required frames, and the small videos have been extracted to individual UHD photos using Matlab image tools. Leica Photogrammetric Suite (LPS) software has been used for all processing steps, except the automatic filtration of the generated tie points, which has been carried out using self-developed Matlab algorithm for epipolar geometry and 2D transformation based filters. Results show that DEM's with quality of nearly 1.2 to 2 decimeter in plane and elevation, respectively can be obtained using DJI Mavic 2 PRO drone, 4K UHD video taken by Hasselblad L1D-20C 20 MP camera, pixel ground footprint of 8 cm, and flight height of 350 m. This level of accuracy is appropriate for many engineering applications, such as initial-planning projects stretched on huge areas, urban development plans, GIS data collection, inventory of earth works materials, and 3D modeling. The obtained quality of the generated DEM depends on the flight height and the camera quality, IOE's, and resolution. Tests show that using 4K UHD video for photogrammetric applications can provide UHD extracted frames, similar to that captured singly, especially with fit flight speed and camera settings, namely: ISO sensitivity, shatter speed, and aperture size. Also, using video facilitates the aerial photography process, overcoming the difficulties of determining the suitable capturing time and location of individual photos in site. The other advantage is the ability of taking alternative frames if the selected images are not suitable for photogrammetric works in terms of tilting and blurring. The opportunity of changing the overlapping rates across the route is another important advantage of using video, especially for curvy routes. Moreover, using different groups of overlapped images for the same route helps for creating different DEM's for the same area, resulting more precise and dense topographic surveying works.

Comparison between Multi Epipolar Geometry & Affine 2d Transformation-Based Filters for Optical Robot Navigation

Abstract: In previous research papers, Multi Epipolar Geometry-based Filter (M-EGF) has proven its high capability to overcome Single Epipolar Geometry-based Filter (S-EGF) as well as with conformal 2D Transformation-based Filter (C-2DF) in terms of providing precise, trusted, outlier-free, and real time Automatic Image Matching (AIM) results for Optical Robot Navigation (ORN) applications. This paper comes in a series of comparing M-EGF with the most common filters extensively used in ORN. Affine 2D Transformation-based Filter (A-2DF) is another familiar filter used for detecting outliers in AIM results and regards as the advanced version of C-2DF, where it can deal with any changing or distortion in image scales in X and Y directions. In this paper, M-EGF has been compared with A-2DF using the same system, tests, tracks and images and the same evaluation techniques used for comparing M-EGF to S-EGF and C-2DF in the related research papers. Tests show that A-2DF is similar to C-2DF in terms of its disability to filter AIM results in areas with open, narrow, and confused Depth Of Field (DOF). A-2DF is also limited in terms of finding out the 6 correct parameters for its mathematical model when AIM results includes a significant number of mismatching points. Difficult view angles has also a noted effect on the performance of A-2DF, but less than that of C-2DF due to its ability to work with different scales. In tests including limited DOF and low level of outliers, A-2DF has shown comparatively adequate outcomes, that is suitable for non-sensitive applications, in which the error does not entail any serious consequences. A-2DF is independent of the errors in Exterior Orientation Parameters (EOP) and Interior Orientation Elements (IOE) of cameras, where it is image points dependent estimation filter. Tests show that M-EGF is time- effective, efficient with any AIM findings, regardless DOF, capturing angle, outliers rate in observations, type of features and tracks. Unlike, A-2DF, tests show that the performance of M-EGF can affect by the quality of IOEs and EOPs, as a number of correctly matched points might be rejected, and this limitation is not related to the filter mathematical design but the professionalism of cameras calibration and EOP determination. in terms of processing time, A-2DF is considerably slow comparing with M-EGF due to its iterative and repeatability design, which makes it, unlike MEGF, unsuitable for real-time precise ORN applications. Keywords: Optical Robot Navigation, Epipolar Geometry, Automatic Image Matching, Co-planarity Equation, Real Time Applications, Affine 2D Transformation

Comparison Between Multi Epipolar Geometry and Conformal 2d Transformation-Based Filters for Optical Robot Navigation

Abstract: This research paper comes in a series of comparisons between the Multi Epipolar Geometry-based Filter (M-EGF) and the common filters that are extensively used in Optical Robot Navigation (ORN) for filtering the results of Automatic Image Matching (AIM). The accuracy of ORN depends mainly on the quality of the AIM results. Conformal 2D transformation-based Filter (C-2DF) is a common filter used in ORN applications. However, C-2DF is limited in terms of: time processing, disability to deal AIM data with significant number of outliers, dealing with images taking from different Depths Of Fields (DOF) and difficult view angles. M-EGF has been introduced recently by the author and compared with Single Epipolar Geometry based Filter (S-EGF), showing high ability to provide ORN with precise, trusted, outlier-free, and real time observations. In this paper, M-EGF has been compared with C-2DF using images captured by optical navigation system simulating ORN, which includes 3 cameras synchronized using GPS time. The performance of the two filters has been evaluated in different AIM environments and the automatically filtered results have been compared to precisely manually reviewed matched points using Matlap. Tests show that C-2DF has failed to deal with the AIM results in areas with open, narrow, and confused DOF. Also, they have failed to find out the right mathematical model in data with high rate of mismatched points and images with difficult view angles. C-2DF is also limited in its capability to deal with figures including different scales. With limited DOF and limited rate of errors, C-2DF has provided relatively sufficient results, which can be suitable for ORN in terms of quality and processing time. C-2DF overcomes S-EGF and M-EGF in terms of being not affected by errors in the Exterior Orientation Parameters (EOP) and Interior Orientation Elements (IOE) of cameras, as C-2DF depends on estimating the mathematical model parameters using only image points.

Multi and single epipolar geometry-based filters vs. affine and conformal 2D transformation-based filters

The accuracy of Optical Robot Navigation (ORN) depends mainly on the quality of the Automatic Image Matching (AIM) results. Conformal 2D transformation-based Filter (C-2DF), affine 2D transformation-based Filter (A-2DF) and Single Epipolar Geometry-based Filter (S-EGF) are common filters used in ORN. Multi-Epipolar Geometry-based Filter (M-EGF) has been introduced, tested and evaluated by the author and compared by each filter of those mentioned above in separate research papers. This paper comes to include all these individually comparisons, with additional details, showing the advantages and limitations of all filters comparing to each other. Tests show that C-2DF and A-2DF have failed to deal with AIM results in areas with open, narrow, and confused DOF. Also, they have failed to find out the right mathematical model in data with high rate of mismatched points and data obtained from images with difficult view angles. With limited DOF and low rate of errors, C-2DF and A-2DF have provided relatively sufficient results, which can be used for ORN applications that do not require precision. A-2DF is relatively better than C-2DF due to its flexibility to deal with figures including different scales, which is the case when dealing with different levels of DOF and different capturing angles between the cameras. The processing time is another disadvantage of C-2DF and A-2DF, where these are based on iterative estimation methods. Tests display how A-2DF is slowest, which keeps it away from using with real time ORN applications. Tests show that S-EGF and M-EGF are timesaving and able to deal with any AIM results, regardless the DOF, view angle and errors rate in observations. S-EGF is affected in areas including lines parallel to the cameras base line. M-EGF has offered the best results in terms of providing error-free filtered matched points in all tests. This can be attributed to the high restriction level of this filter, where the probability for the mismatched point to pass throughput the three co-planarity equations is nearly zero. M-EGF and S-EGF are affected by the quality of the Interior Orientation Elements (IOEs) and Exterior Orientation Parameters (EOPs) of the three cameras, leading to rejection a small number of corrected matched points, which can be avoided with professionally manufactured ORN systems. Tests illustrated that S-EGF and M-EGF are extremely high-speed and S-EGF is the faster and M-EGF, C-2DF, and A-2DF comes after, respectively. All results indicated that M-EGF is the best, as it is fast, restricted, reliable, and error-free technique and is suitable for real-time precise ORN applications.

Method for Determining Elements of Internal Orientation Calibration in Multi-Matrix Optoelectronic Devices

In the operation schemes of optical electronic devices (OED), such as digital autocollimators, direction finders, Shack-Hartmann sensors, as well as astro-orientation systems, projection measuring systems, geometric calibration schemes for OED, the photo-detector acts not only as a receiving device, but also as a measuring device. The tasks facing the OED photo-detectors. The solution to the problem is the use of several photo-detectors installed on one electronic board. Since OED photo-detectors act, inter alia, as measuring devices, it is necessary to perform their geometric calibration. Geometric calibration involves the measurement of interior orientation parameters used in the processing of OED images. Geometric calibration makes it possible to eliminate errors in mutual exposure of photo-detectors on one electronic board installed in the focal plane, as well as distortions introduced by the OED lens, primarily by distortion. The correctness of the interior orientation parameter determination is influenced by the relative position of the collimator, with the help of which the geometric calibration is performed, and the calibrated OED itself, i. e. the external orientation elements. The task is to separate the interior orientation parameters and the elements of external orientation. This is achieved using the method of mathematical processing of measured data in the forward and inverted positions of the collimator. This method of geometric calibration allows to use it for geometric calibration of OED with a large number of photo-detectors. The paper presents the results of the geometric calibration of the interior orientation parameters when the collimator projects a test object onto three photo-detectors of the OED layout. The factors influencing on the accuracy of the geometric calibration of the interior orientation elements for OED are determined in the paper. The developed method for geometric calibration of the interior orientation parameters for multi-matrix OED provides high measurement accuracy – not more than 0.1''–0.2''.

OPTIMIZATION ALGORITHM OF TILTED IMAGE MATCHING BASED ON ADAPTIVE INITIAL OBJECT ASPECT

Abstract. When adopting the matching method of the least squares image based on object-patch to match tilted images, problems like the low degree of connection points for images with the discontinuity of depth or the discrepancy in elevation or low availability of aerotriangulation points would frequently appear. To address such problems, a tilted-image-matching algorithm based on an adaptive initial object-patch is proposed by this paper. By means of the existing initial values of the interior and exterior orientation elements of the tilted image and the information of object points generated in the matching process, the algorithm takes advantage of the method of multi-patch forward intersection and object variance partition so as to adaptively calculate the elevation of the object-patch and the initial value of the normal vector direction angle. Furthermore, this algorithm aims to solve the problem of difficulties in matching the tilted image with its corresponding points brought about by the low accuracy of the initial value of the tilted image when adopting the matching method of the least squares image based on object-patch to match the tilted image with high discrepancy in elevation. We adopt the algorithm as proposed in this paper and the least squares image matching method in which the initial state of the object-patch is horizontal to the object-patch respectively to conduct the verification process of comparing and matching two groups of tilted images. Finally, the effectiveness of the algorithm as proposed in this paper is verified by the testing results.

Алгоритм определения элементов ориентирования тепловизионного снимка с беспилотного летательного аппарата по опорным точкам

The article deals with the algorithm for determining the exterior and interior orientation elements of an infrared image obtained from an unmanned aerial vehicle using four reference points. The idea of the proposed algorithm is to determine the true position of the image by the defined three-dimensional spatial coordinates of the reference points in the image at the time of shooting. The image plane is built up on the defined points. The coordinates of the principal point of the image are calculated by making a perpendicular from the perspective center to the plane of the image. The focal length is equal to the length of this perpendicular. Euler angles characterizing the position of the camera at the time of shooting are calculated after determining the axes’ directions of the inclined image coordinate system. The proposed algorithm is effective even in the case when all the elements of the image orientation are unknown. Calculations of the image elements on model examples with different initial data show high accuracy. The possibility of obtaining the necessary accuracy for the orthotransformation procedure was confirmed on real images.

High Sensitive Night-time Light Imaging Camera Design and In-orbit Test of Luojia1-01 Satellite.

Luojia1-01 satellite is the first scientific experimental satellite applied for night-time light remote sensing data acquisition, and the payload is an optical camera with high sensitivity, high radiation measurement accuracy and stable elements of interior orientation. At the same time, a special shaped hood is designed, which significantly improved the ability of the camera to suppress stray light. Camera electronics adopts the integrated design of focal plane and imaging processing, which greatly reduces the volume and weight of the system. In this paper, the design of the optical camera is summarized, and the results of in-orbit imaging performance tests are analyzed. The results show that the dynamic modulation transfer function (MTF) of the camera is better than 0.17, and the SNR is better than 35 dB under the condition of 10 lx illuminance and 0.3 reflectivity and all indicators meet the design requirements. The data obtained have been widely applied in many fields such as the process of urbanization, light pollution analysis, marine fisheries detection and military.

BUILDING SHADOW DETECTION FROM GHOST IMAGERY

Abstract. Shadow is one of the basic features of remote sensing image, it expresses a lot of information of the object which is loss or interference, and the removal of shadow is always a difficult problem to remote sensing image processing. In this paper, it is mainly analyzes the characteristics and properties of shadows from the ghost image (traditional orthorectification). The DBM and the interior and exterior orientation elements of the image are used to calculate the zenith angle of sun. Then this paper combines the scope of the architectural shadows which has be determined by the zenith angle of sun with the region growing method to make the detection of architectural shadow areas. This method lays a solid foundation for the shadow of the repair from the ghost image later. It will greatly improve the accuracy of shadow detection from buildings and make it more conducive to solve the problem of urban large-scale aerial imagines.

EMERGENCY RESCUE MANAGEMENT SUPPORTED BY UAV REMOTE SENSING DATA

Abstract. In the proposed SAFEDAM system, aerial and satellite-based information is used for the monitoring of river bodies, flood monitoring during the event, and for post-disaster damage assessment. UAV constitute a valuable source of information about the current situation in the field during the operation of emergency services. Time is crucial, and the basic assumption to use UAV remote sensing data is to make them available immediately after landing. Therefore, the approach of automatic orthomosaics created based on the exterior orientation of the transmitted images using direct georeference was selected instead of sophisticated automatic on-the-fly image-matching and georeferencing. The article conveys the justification for selecting this option in order to process orthomosaics with lower localisation accuracy in a short time. The developed algorithm takes into account the elements of exterior and interior orientation of the camera as well as the digital terrain model. The evaluation of the orthomosaic was conducted based on theorthophoto created in post-processing. Thanks to the approach used, images from the platform are available in the near real time on the screen of the interventional mode of the SAFEDAM system and are an extremely valuable and informative source of data. The system also integrates tools, which support the management of the action and prepares site documentation.

Measurement and Precision Analysis of Exterior Orientation Element Based on Landmark Point Auxiliary Orientation

Obtaining the interior and exterior orientation elements and distortion parameters of camera is critical in the applications of photogrammetric survey and computer vision on recovering object position and angular orientation. While being used outside as supervision devices monitoring objects in the air, cameras are generally installed in non-calibration designated regions with high erection and elevation postures within their view distance over the sky. Therefore, it is really hard to obtain the exterior orientation element of camera. In order to solve this problem, this paper proposed a method to obtain the exterior orientation element of camera outdoors by applying landmark point auxiliary orientation and to obtain the interior and exterior orientation elements and distortion coefficient of camera by using self-check bundle adjustment in indoor three-dimensional control field. Thus, the transformational relations between the landmark points of different positions could be calculated according to the method of landmark point auxiliary orientation. The exterior orientation elements of camera could be recovered through transformational relations, and the position and posture of recovered camera in outdoor non-calibration designated field could be simulated accordingly. The experiential results show that the exterior orientation elements of camera can be effectively recovered through the method of landmark point auxiliary orientation while certain high intersection precision can be maintained.

Robust Approach for Recovery of Rigorous Sensor Model Using Rational Function Model

The replacement of the rational function model (RFM) by the rigorous sensor model (RSM) has been studied extensively and verified with many types of sensors and remote-sensing applications. However, relatively less research has been conducted on recovering RSM from RFM, and the few relating techniques can only be applied in specific circumstances. This paper proposes a novel linear method to obtain the position, attitude, and interior orientation (IO) elements of satellites based on the orientation information of the rays implied by the RFM. Instead of resection, forward intersection is used to solve for position, and an equivalent body coordinate system is introduced to overcome the strong correlation between the attitude and IO. The orientation information of the rays implied by the RFM is used to calculate the IO pixel by pixel. Experiments using the Ziyuan 3 panchromatic nadir sensor show that this method can recover the exterior orientation and IO elements effectively.

GEOPOSITIONING PRECISION ANALYSIS OF MULTIPLE IMAGE TRIANGULATION USING LRO NAC LUNAR IMAGES

Abstract. This paper presents an empirical analysis of the geopositioning precision of multiple image triangulation using Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) images at the Chang’e-3(CE-3) landing site. Nine LROC NAC images are selected for comparative analysis of geopositioning precision. Rigorous sensor models of the images are established based on collinearity equations with interior and exterior orientation elements retrieved from the corresponding SPICE kernels. Rational polynomial coefficients (RPCs) of each image are derived by least squares fitting using vast number of virtual control points generated according to rigorous sensor models. Experiments of different combinations of images are performed for comparisons. The results demonstrate that the plane coordinates can achieve a precision of 0.54 m to 2.54 m, with a height precision of 0.71 m to 8.16 m when only two images are used for three-dimensional triangulation. There is a general trend that the geopositioning precision, especially the height precision, is improved with the convergent angle of the two images increasing from several degrees to about 50°. However, the image matching precision should also be taken into consideration when choosing image pairs for triangulation. The precisions of using all the 9 images are 0.60 m, 0.50 m, 1.23 m in along-track, cross-track, and height directions, which are better than most combinations of two or more images. However, triangulation with selected fewer images could produce better precision than that using all the images.

GEOPOSITIONING PRECISION ANALYSIS OF MULTIPLE IMAGE TRIANGULATION USING LRO NAC LUNAR IMAGES

This paper presents an empirical analysis of the geopositioning precision of multiple image triangulation using Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) images at the Chang’e-3(CE-3) landing site. Nine LROC NAC images are selected for comparative analysis of geopositioning precision. Rigorous sensor models of the images are established based on collinearity equations with interior and exterior orientation elements retrieved from the corresponding SPICE kernels. Rational polynomial coefficients (RPCs) of each image are derived by least squares fitting using vast number of virtual control points generated according to rigorous sensor models. Experiments of different combinations of images are performed for comparisons. The results demonstrate that the plane coordinates can achieve a precision of 0.54 m to 2.54 m, with a height precision of 0.71 m to 8.16 m when only two images are used for three-dimensional triangulation. There is a general trend that the geopositioning precision, especially the height precision, is improved with the convergent angle of the two images increasing from several degrees to about 50°. However, the image matching precision should also be taken into consideration when choosing image pairs for triangulation. The precisions of using all the 9 images are 0.60 m, 0.50 m, 1.23 m in along-track, cross-track, and height directions, which are better than most combinations of two or more images. However, triangulation with selected fewer images could produce better precision than that using all the images.

Assessing the Accuracy of Ortho-image using Photogrammetric Unmanned Aerial System

Abstract. Smart-camera can not only be operated under network environment anytime and any place but also cost less than the existing photogrammetric UAV since it provides high-resolution image, 3D location and attitude data on a real-time basis from a variety of built-in sensors. This study’s proposed UAV photogrammetric method, low-cost UAV and smart camera were used. The elements of interior orientation were acquired through camera calibration. The image triangulation was conducted in accordance with presence or absence of consideration of the interior orientation (IO) parameters determined by camera calibration, The Digital Elevation Model (DEM) was constructed using the image data photographed at the target area and the results of the ground control point survey. This study also analyzes the proposed method’s application possibility by comparing a Ortho-image the results of the ground control point survey. Considering these study findings, it is suggested that smartphone is very feasible as a payload for UAV system. It is also expected that smartphone may be loaded onto existing UAV playing direct or indirect roles significantly.

Assessing the Accuracy of Ortho-image using Photogrammetric Unmanned Aerial System

Smart-camera can not only be operated under network environment anytime and any place but also cost less than the existing photogrammetric UAV since it provides high-resolution image, 3D location and attitude data on a real-time basis from a variety of built-in sensors. This study’s proposed UAV photogrammetric method, low-cost UAV and smart camera were used. The elements of interior orientation were acquired through camera calibration. The image triangulation was conducted in accordance with presence or absence of consideration of the interior orientation (IO) parameters determined by camera calibration, The Digital Elevation Model (DEM) was constructed using the image data photographed at the target area and the results of the ground control point survey. This study also analyzes the proposed method’s application possibility by comparing a Ortho-image the results of the ground control point survey. Considering these study findings, it is suggested that smartphone is very feasible as a payload for UAV system. It is also expected that smartphone may be loaded onto existing UAV playing direct or indirect roles significantly.

THE OUTDOOR RAPID CALIBRATION TECHNIQUE AND REALIZATION OF NONMETRIC DIGITAL CAMERA BASED ON THE METHOD OF MULTI-IMAGE DLT AND RESECTION

For non-metric CCD digital camera features and the needs of Rapid field non-metric cameras calibration, the error sources was detailed analyzed and a mathematical calibration model has been founded. Both detailed multi-image group iterative method for solving DLT coefficient, the elements of interior orientation and distortion parameters of lens and the multi-image resection method for solving the elements of interior orientation, elements of exterior orientation and distortion parameters of lens have been discussed. A standard steel cage (e.g. Figure 1) has been made for real calibrating non-metric cameras outdoor quickly. In order to verify the accuracy, each method mentioned has been used to solve elements of interior orientation and distortion parameters with the same camera (e.g. Figure 2) and the same test images. The results of accuracy show that the maximum X error was 0.2585mm, the maximum Y error was 0.6719mm and the maximum Z error was 0.1319mm by using multi-image DLT algorithm. On the other hand, the maximum X error was 0.1914mm, the maximum Y error was 0.9808mm and the maximum Z error was 0.1453mm by using multi-image resection algorithm. The forward intersection accuracy of the two methods was quite, and the both were less than 1mm. By using multi-image DLT algorithm the planimetric accuracy was less than 0.2585mm and the height accuracy was less than 0.6719mm. On the other hand, by using multi-image resection algorithm the planimetric accuracy was less than 0.1914mm and the height accuracy was less than 0.9808mm. The planimetric accuracy of resection algorithm was the better than DLT algorithm, but the elevation accuracy of DLT algorithm was the better than resection algorithm. In summary both method can be accepted for nonmetric camera calibration. But also the solver accuracy in the inner orientation elements and distortion parameters was not very high has been noted. However for non-metric camera, the true value of inner orientation elements and lens distortion were unknown did not affect the accuracy of photogrammetry.