Table of Content

    25 April 2019, Volume 21 Issue 4 Previous Issue    Next Issue
    Orginal Article
    The Impact of UAV Remote Sensing Technology on the Industrial Development of China: A Review
    Lei YAN, Xiaohan LIAO, Chenghu ZHOU, Bangkui FAN, Jianya GONG, Peng CUI, Yuquan ZHENG, Xiang TAN
    2019, 21 (4):  476-495.  doi: 10.12082/dqxxkx.2019.180589
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    The drone is a data-driven air mobile agent in the future network environment, UAV remote sensing technology has become one of the leading industries for UAV applications. This paper introduces the development of UAV remote sensing technology within China and internationally, and there is a particular focus on the development of UAV remote sensing technology within China from the "10th Five-Year Plan" to the "13th Five-Year Plan" since the 21st century. It also focuses on the UAV remote sensing calibration field, the establishment of aerospace calibration field and application verification are also described, including the development of load and system technology of UAV remote sensing system. Secondly, it will introduce the industrial application of UAV remote sensing technology in the fields of national defense, land and ocean island reef mapping, geological disaster monitoring, and emergency rescue. At last, China's advancement in UAV remote sensing technology with regards to intelligent control of networking, accuracy and real-time metric basis, self-organizing redundant fault tolerance of load platform, remote sensing big data cloud processing technology, and the practical application of UAV remote sensing networking will also be discussed. The overall goal of the future development of UAV remote sensing is to establish an unmanned aircraft network observation system with rapid information acquisition capability, to realize the unmanned aircraft networking technology from the project level to the remote sensing industry. At the same time, it also lays a foundation for Chinese national strategic leap in becoming a strong power in remote sensing field.

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    Current Status and Application Prospect Analysis of VTOL-UAVs for Remote Sensing Applications in China
    Menglin YANG, Daochun LI, Zhiqiang WAN, De YAN, Yaokun WANG
    2019, 21 (4):  496-503.  doi: 10.12082/dqxxkx.2019.180422
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    In recent years, demand of unmanned aerial remote sensing tools is growing for ecological environment, flood disaster emergency response, land security monitoring and other remote sensing observation tasks. Building heterogeneous UAV remote sensing observation multi-task cluster system is the development goal in recent years. In order to complete the ecological construction of UAV remote sensing, vertical take-off and landing UAV plays an increasingly important role in many fields because of its characteristics of fast patrol and taking-off and landing without site restrictions. The main contents of this paper include the research on the development status of domestic vertical take-off and landing UAV, the analysis of UAVs for the aviation remote sensing application market and the introduction of typical UAV models, the application scenarios and case analysis of the vertical take-off and landing UAV in the field of remote sensing, and the application prospects and development trends of the vertical take-off and landing UAV in the field of remote sensing. Through extensive research and in-depth analysis, it is known that the vertical take-off and landing UAVs with fixed-wing are gradually replacing the dominant position of multi-rotor aircraft; vertical take-off and landing UAVs occupy 80.47% of the market share of remote sensing application drones; Diversified power, intelligent system, diversified layout, and small size are the development direction of vertical take-off and landing UAVs for remote sensing applications. This paper comprehensively expounded and analyzed the related content of vertical take-off and landing UAVs for remote sensing applications, and provides reference and support for the ecological construction of remote sensing aviation drones.

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    The Present Situation and Prospect of Aerostat Applied to Remote Sensing and Remote Survey in China
    Guilin PENG, Zhiqiang WAN
    2019, 21 (4):  504-511.  doi: 10.12082/dqxxkx.2019.180390
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    The aerostat is a new airborne remote sensing platform, which is suitable for high resolution remote sensing in a small and medium area. The floating aircraft, especially the medium and low altitude small remote control airship, can be supported by the power propulsion and control system to implement the maneuvering flight. It has the characteristics of long flight time, large coverage area, strong load capacity, and high cost-efficiency. Satellite remote sensing data that lacks high spatial resolution and timeliness is of limited ability to access remote environment at a micro scale. Rotary or fixed-wing unmanned aerial vehicle (UAV) platforms, which is capable of performing unmanned inspection, surveillance, reconnaissance, and mapping of inimical areas with amateur or SLR digital cameras, can fly with manual, semi-automated, and autonomous modes. It is well known that recently UAVs in the geomatics field became a common platform for data acquisition, but the platforms have a low payload capacity and its flight was too short to be a valid complementary solution to data acquisitions. Compared with several other aviation platforms, the airship platform has a comprehensive advantage, which meets the comprehensive urgent needs and precision large scale mapping requirement for the areas with complex terrains. It has a wide application prospect in various fields, such as basic geographic data collection, land resources exploration, environmental monitoring, and agricultural vegetation monitoring. As its height superiority,the airship can effectively overcome the influence of earth curvature and the environment which helps to enhance the detection performance. Near space aircraft is the fundamental infrastructure platform in breaking down the natural barriers between the aviation region and the outer space. The stratosphere airship, which is one of the quasi-static aircrafts within the near space, has unique platform advantages. It is equipped with laser scanner, VIS camera (one for vertical capturing or more for slope capturing), thermo camera, and INS/GPS as an exterior orientation (pose) determination in undertaking tasks of aviation thermometric mapping and environmental studies. This objectives of this paper are (1) to analyze the application cases of the remote sensing telemetry of China's human aircraft, UAV, middle and low altitude airship and stratospheric airship platform; (2) to analyze the performance characteristics, working methods, and technical difficulties of each aviation platform; (3) to compare the technical features of various platforms; (4) to discusse the advantages of the application of the small and medium remote control airship platform in remote sensing telemetry, and (5) to explore the development status and key technology of the stratospheric airship. In the end, the future application of the remote aerostat is prospected in the light of the research progress in the international related fields.

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    The Use of UAV Remote Sensing Technology to Identify Crop Stress: A Review
    Yaohuan HUANG, Zhonghua LI, Haitao ZHU
    2019, 21 (4):  512-523.  doi: 10.12082/dqxxkx.2019.180397
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    Crop stress is an important factor restricting global agricultural development. Monitoring and understanding rapid, large-scale and real-time crop stress is of great significance for agricultural production. However, traditional methods of crop stress monitoring (such as fields surveys, physical and chemical detection, and satellite remote sensing), are strongly influenced by field and atmospheric conditions, temporal and spatial resolution, and labor costs. Rapid development of UAV platforms and various lightweight sensors, provide new solutions for various crop stress monitoring. These offer multiple advantages, primarily high frequency and speed. The introduction of various mainstream UAV platforms such as multi-rotor and fixed-wing, and sensors such as visible light digital camera, multispectral camera, hyperspectral camera, and thermal infrared camera has allowed for more efficient crop monitoring. This review explores the main biotic and abiotic stress types used by UAV remote sensing systems for crop monitoring. Biotic stressors mainly include miscellaneous grass stress, plant diseases, and insect pests stress. Abiotic stressors predominantly include water and nutrient stress. The application and technical methods of UAV remote sensing system monitoring of crop stress, based on spectral imaging and thermal infrared sensor technology are discussed. Sensitive bands and common vegetation indices used for crop stress monitoring are identified. Finally, key issues associated with UAV remote sensing and the future use of UAV remote sensing for crop stress monitoring are discussed. The advancement of UAV remote sensing technology, could contribute to improved identification and monitoring of crop stress in the near future.

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    Development of Ka-band Miniature Synthetic Aperture Radar based on UAV
    Qi ZHANG, Lei ZHANG, Jundong GUO, Jianmin HU
    2019, 21 (4):  524-531.  doi: 10.12082/dqxxkx.2019.180453
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    Unmanned Aerial Vechicle (UAV) is widely used in military investigation and attack, land and resources survey, disaster monitoring and other fields because of its advantages such as long stay time and easy maintenance. Synthetic aperture radar (SAR) is a kind of two-dimensional imaging radar, which can obtain radar images similar to optical images. It has the advantages of all-weather, high resolution, wide detection range and so on. It is one of the important loads of UAV. However, due to the relatively small space and load capacity of UAV, radar load must be small volume, light weight and low power consumption. Ka-band electromagnetic wave signal has the characteristics of short wavelength, wide bandwidth and small size of key microwave devices. It is suitable for high resolution miniature radar load. In 2015, the Institute of Electronics, Chinese Academy of Sciences, developed a kind of high resolution Ka-band synthetic aperture radar for small or medium UAV. The performance of the SAR was verified by flight test. In this paper, the key technologies of Ka-band SAR radar system are studied. The design scheme of radar system and key modules, the parameter of each working mode and real-time imaging algorithm are introduced. The radar weight is less than 10 Kg, and the peak power consumption is less than 100 W. It is suitable for small or light UAV. The high-resolution flight images obtained by the radar on light flight platform are displayed, and the performance of the images are analyzed. The experimental results show that the Ka-band SAR system can generate clear radar image and meets the design requirements. For example, the image resolution is better than 0.2 m and the detection distance is greater than 10 km..The rapid progress of microwave device technology represented by solid-state high power amplifier is the foundation of the success of this project. The project is a new attempt to develop Ka-band SAR and apply it to UAV. It also makes a useful exploration for the further development of Ka-band synthetic aperture radar and has important application value. The development of small Ka-band synthetic aperture radar in the future depends on the maturity of semiconductor technology and the improvement of the performance of Ka-band microwave devices. On the other hand, it also depends on the research of new style SAR which has high duty cycle and pulse agility, which can improve the average power of radar and solve the problem of ambiguity of detection range.

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    Remote Sensing Maneuvering Observation Attitude Control of Quadrotor Aircraft based on Sliding-mode and ESO
    Shike LONG, Shanlin SUN, Haimeng ZHAO
    2019, 21 (4):  532-541.  doi: 10.12082/dqxxkx.2019.180503
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    With the promotion of UAVs in the application fields of various industries, especially in remote sensing, the demand for precision remote sensing is becoming more and more intense. As a kind of UAV, quad-rotor has developed rapidly in recent years and has become the first choice for small-scale accurate remote sensing mapping. However, its own flight stability is directly related to the remote sensing imaging effect, and the attitude controller therefore becomes the basic problem of the research on the stability of UAVs. For the under-actuated,strong coupling and nonlinear characteristics of quad-rotor aircraft movement, a method of attitude controller based on sliding mode and extended state observer (ESO) was presented. A series of experiments methods were designed to obtain the model parameters: inertia, lift coefficient, torque coefficient and time constant of the motor, and establish a mathematical model of each module of the four rotors. The sliding mode controller was used to achieve quad-rotor aircraft attitude decoupling robust control, the symbol function was replaced by sat function to improve sliding mode controller structure and slow down flutter phenomenon. Combined with extended state observer (ESO), the sum of quad-rotor attitude loop system interference can be estimated at real-time. The sum of interference includes states coupling terms, un-modeled dynamics and external disturbances. Thus the disturbance compensation was added into sliding mode control output in real-time to achieve high quality quad-rotor attitude control. Two sets of experiments were designed. One set of experiments was the actual manipulation command tracking experiment, and the other set was the actual external load interference experiment. The two quad-rotor UAV attitude controllers (sliding mode controller based ESO&individual sliding mode controller) are compared with the simulation and the actual test flight based on experiments. The experimental results show that, under the same conditions, the controller based on sliding mode and extended state observer (ESO) can achieve stable attitude control and reduce tracking error by about 20%, and the control method can enhanced the anti-interference ability of the quad-rotor. while quad-rotor hovering, it can reduces the fluctuation of the attitude angle by about 50%, which has practical application value.

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    Research on the Redundancy Fault-tolerant Algorithm of Altitude Safety Monitoring for Remote Sensing Networking Flight of Light and Small UAVs
    Yongjun WANG, Zhi LI, Shanlin SUN, Xingyuan MA, Lei YAN
    2019, 21 (4):  542-551.  doi: 10.12082/dqxxkx.2019.180502
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    To satisfy the altitude safety monitoring for remote sensing networking flight of light and small Unmanned Aerial Vehicles (UAVs), a multi-source information redundancy measurement scheme based on INS/GPS/ barometer is designed in this paper. By analyzing the requirement of UAV reliability and fault tolerance in the complex and changeable working environment of remote sensing network application, the federated filtering algorithm is adopted to fuse the redundant information of multi-sensor. In this paper, the structure and algorithm of federated filtering are analyzed, and the principle of selecting information allocation coefficients with good fault-tolerance and high filtering accuracy is obtained. Then a Pignistic probabilistic transformation fault-tolerant information allocation method based on information entropy is proposed. This algorithm can obtain a clear and accurate fault probability distribution, from which the system fault probability is determined by information entropy . Then the weight ratio of each subsystem of the group measurement system is obtained by combining the value principle of information allocation coefficient. Simulation results show that different information allocation coefficients mainly affect the estimation error and fault-tolerant performance of subsystems, but which have little influence on the fusion estimation error of federated main filter. It shows that the fault-tolerant information allocation method in this paper can provide reliable allocation coefficients for each subsystem component. The fixed-altitude hovering experiment on the multi-rotor UAV platform proves that this method can be used to reduce the altitude error of UAV to one quarter of the traditional federated filtering algorithm, which further proves that this method can be used to improve the accuracy and fault-tolerance of the UAV altitude safety monitoring system.

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    Redundancy-Based Fault-Tolerance Control Schemes in UAV Networking for Real-Time Remote Sensing Monitoring Missions
    Ullah Sana, Lei YAN, Zhaohui FENG, Haimeng ZHAO, Yiyuan SUN, Hongying ZHAO
    2019, 21 (4):  552-559.  doi: 10.12082/dqxxkx.2019.180389
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    Small to medium-sized unmanned aerial vehicles (UAVs) are increasingly been used in various real time static and dynamic missions, which make them very useful tool to assist men. There are several factors which make these UAVs suitable for monitoring and survey in a wide range of conditions. Despite of all these capabilities, certain factors remain the biggest challenge for extensive use of UAVs at individual level in different real-time missions. Moreover, once prompt response to any of these constraints during the mission execution is missed, can affect the mission’s overall results, leading to partial or complete failure of the whole mission. For such purpose introduction of redundant fault-tolerance into the system is very important in order to minimize the probability of failures and increase its robustness because it is practically impossible to build a perfect system. The fundamental problem is that, as the complexity of a system increases, its reliability drastically decreases unless compensatory measures are taken. The aim of redundant fault tolerance is to introduce redundancy by adding one or more modules as back-up usually in parallel configuration. To improve the robustness and success rate of UAV network systems for aerial remote sensing missions under extreme conditions, this paper introduced the redundancy-based fault-tolerance control technology into UAVs networking designs, and determined the best networking solutions with different restrictions. The devised networking design includes multi-UAV network with active cooperation through simultaneous monitoring during remote sensing missions such as "large-scale ecological monitoring," "medium-scale flood disaster monitoring," and "fine-scale security surveillance" under different observation conditions. The multi-UAV network serve as redundant fault-tolerant architecture where system could be fault tolerant through adding more than one UAVs as back-up. Scenarios set for the redundant fault-tolerance are UAVs position and viewing angle during different extreme conditions. The UAV(s) in network scheme is considered faulty when its position and viewing angle exceeds the set threshold and would be separated and not considered for further analysis. Only in this way, we can get effective output of the networking control solutions under extreme conditions to ensure that missions can be carried out smoothly.

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    Statistical Analysis Technology of UAS Cloud Data Exchange Platform based on Big Data
    Yiqin BAI, Xinfeng CHEN, Junfeng YUAN
    2019, 21 (4):  560-569.  doi: 10.12082/dqxxkx.2019.180395
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    After several years of development, light and small unmanned aircraft systems (UASs) have been widely used in various industries both in China and many other countries. However, the UASs have many models, with scattered equipments and no systematic management. Meanwhile, some safety issues exist. This urgently requires the relevant regulatory authorities to regulate, supervise, and maintain safe flight operations by taking their operating rules and characteristics into account. In order to standardize the operation of light and small civil UASs across the country and promote the industry development, the Civil Aviation Administration of China has issued the "Provisions for the Operation of Light and Small Unmanned Aircraft (for Trial Implementation)" advisory circular and the "Specification for Interface Data of Unmanned Aircraft System Cloud System". The UAS cloud data exchange platform was developed in 2016, and the data sharing of multiple UAS cloud systems in China was realized. With this platform the UASs registered in different UAS cloud systems are visible to each other in the same airspace, which improved the flight safety of China's low-altitude airspace. However, with the rapid development of the application of the unmanned aerial vehicle (UAV) industry, the number of UAVs supervised by the Civil Aviation Authority and the data on the operation of the UAVs has increased dramatically, which has also brought great challenges to the traditional data management methods. In this paper, we will describe the current situation of the operation of big data from the UAS cloud data exchange platform in China followed by discussion on the technical bottle necks in the statistical analysis of the operation data of the traditional UAS. Then we will propose a statistical analysis method for the UAS operation data, and establish a framework of statistical analysis of big data from the cloud data exchange platform. In the end, we will outline how to use Apache Spark and Cassandra database to quickly process, store, count, and analyze the massive data generated by the UAS cloud data exchange platform. The research situation of implementing various statistical index algorithms based on the platform is introduced in detail. This research not only improves the efficiency of statistical analysis of UAS operation data, but also provides the operation management rules of China's light and small UASs from multiple dimensions. sWe highlight that the UAS has significant operational characteristics, which are different from general and transportation aviations. This paper provides reference for government and industry decision-making, which has strong practical significance.

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    Construction of a UAV Low-altitude Public Air Route based on an Improved Ant Colony Algorithm
    Chenchen XU, Xiaohan LIAO, Huanyin YUE, Ming LU, Xiwang CHEN
    2019, 21 (4):  570-579.  doi: 10.12082/dqxxkx.2019.180392
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    The ever-increasing numbers of UAVs and their free-flying route planning have brought great challenges to national aviation safety. In order to build a safe and efficient aviation flight environment, it is possible to establish an isolated airspace for the UAV activities, and also plan UAV low-altitude public air routes within it. If established, this would increase safe airspace utilization and provide a decision-basis for UAV traffic management. Taking full account of the geographic characteristics of near-surface flight and the near-instant messaging capabilities of UAVs, this study built a low-altitude flight environment for UAVs in Tianjin, China based on multi-source geospatial data using geographic information technologies, and constructed a low-altitude public air route network using an improved Ant Colony Optimization (ACO) algorithm. The study had five major components. Firstly, we developed a path-searching model by improving the traditional ACO algorithm from search space and local target selection. The improved algorithm can be used to search paths in eight directions along a line between the start and end points in order to shorten the search time, and the search radium was determined by an obstacles ratio. Then, local target selection was optimized by introducing evaluation function of A* algorithm and random roulette method. Secondly, we compared the calculating efficiency and path length between the traditional algorithm and the improved one, and found that the improved algorithm was three times more efficient and shorter than the traditional one. Thirdly, the low-altitude flight environment for UAVs included a cellular network, and climatological condition and airspace-policy can be taken into account. The cellular network environment was determined by the distribution of mobile communication base stations and signal attenuation principles. Climatological conditions included wind shear, thunderstorms, glaciation, and low-visibility weather events, and all of which have a significant impact on UAV flight safety. The airspace-policy factors included populated areas, key buildings, and civil airport clearances. Fourthly, we constructed a digital low-altitude airspace by establishing UAV flight principles within air routes and quantifying a grid cost for each kind of constraint. Lastly, the fifth component is verifying the outcomes’ reliability by comparing air-route length with the most realistic distance that the UAV currently exhibits. In summary, we found that the improved algorithm greatly shortened search time, and reduced path redundancy. The air-route lengths also comply with the farthest-distance requirement for UAVs currently on the markets. The study described basic ideas and key technologies of the UAV's low-altitude public air route research and can provide the core technical support for the UAV control systems.

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    Correction Method of SAR Image Geometric Positioning Parameters based on DEM
    Shucheng YANG, Guoman HUANG, Chunquan CHENG
    2019, 21 (4):  580-587.  doi: 10.12082/dqxxkx.2019.180386
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    For geometric correction of SAR image without ground control point in large area, method of geometric positioning parameters correction based on DEM is proposed in this paper. The basis of this method is that the static error of geometric positioning parameters is stable in short time and certain area. Firstly, simulation SAR Image is generated based on DEM. Then, feature points are extracted on the Simulation SAR Image. Corresponding image point of these feature points on original SAR image are extracted by image matching between simulation Image and original SAR image. And the geographic coordinates of these feature points are got by indirect geolocation with DEM. The image points on original SAR image with geographic coordinates are used for reference points of geometric positioning parameters correction. And then, the correction model is established according to rigorous geometric imaging model of SAR image and correction values of geometric positioning parameters are solved with the reference points. Finally, geometric positioning parameters of other SAR images in certain area are corrected with the values, and geometric correction accuracy of SAR images in this area is improved. GF-3 SAR images were used in experiments. The correction values of geometric positioning parameters were obtained from one image. Geometric positioning parameters of other images in the same orbit and in different orbits were corrected. The geometric positioning accuracy before and after parameters correction was evaluated. Geometric positioning accuracy of the image in the same orbit improved from 66.0 m before parameters correction to 9.7 m after parameters correction, and that of the image in different orbit improved from 65.0m to 13.5 m. The results showed that geometric positioning accuracy can improved significantly by parameters correction using the method of this paper.

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    A Fast Mosaic Algorithm of UAV Images based on Dense SIFT Feature Matching
    Jiabin YANG, Yongtao JIANG, Xingbin YANG, Guangmeng GUO
    2019, 21 (4):  588-599.  doi: 10.12082/dqxxkx.2019.190001
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    The UAV (Unmanned Aerial Vehicle) photography is a new remote sensing system emerging in recent years. It plays an important role in the rapid emergency response of natural disasters. However, due to the large amount of UAV image data, the traditional method for image matching and mosaic is low accuracy and time-consuming. Feature matching is one of key steps in UAV image mosaic. Traditional matching algorithms have several problems, including less feature points, feature maldistribution, and time-consuming. To solve these problems, a fast image mosaic algorithm based on Dense SIFT feature matching is proposed. Firstly, the connection matrix is build based on POS (Position and Orientation System) data to conduct the matching process. The UAV images are then down-sampled. Secondly, image segmentation is performed on the down-sampled images. Then the Dense SIFT operator is used in overlap area of down-sampled images to obtain the initial matching points which are eliminated through matching by the RANSAC (Random Sample Consensus) algorithm and refined by the NCC algorithm on the original and down-sampled images, respectively. Finally, processed images are projected to the object coordinate system based on collinear equation which is calculated by the bundle adjustment method. By contrast, the SIFT (Scale-Invariant Feature Transform) and SURF (Speeded Up Robust Feature) algorithms and the Pix4Dmapper Photogrammetry software are used to test the quality and efficiency of the Dense SIFT algorithm. Two groups of UAV images mosaic experiment results indicate: (1) The Dense SIFT algorithm can be used to obtain about five times more evenly distributed matching points than the SIFT and SURF algorithm at the same time; (2) The Dense SIFT algorithm can be used to effectively improve the quality of the images mosaic by removing the phenomenon of ghosting; (3) It takes about half the time of Pix4D mapper software to complete the same image mosaic test using the Dense SIFT algorithm. This indicates that the presented algorithm has a high image mosaic quality and fast processing speed, which can play an important role in the rapid emergency response of natural disasters.

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    Automatic Retrieval and Position Reconstruction of UAV Oblique Photogrammetry
    Yushan SUN, Haibin AI, Biao XU, Quanye DU
    2019, 21 (4):  600-607.  doi: 10.12082/dqxxkx.2019.180415
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    In recent years, unmanned aerial vehicle (UAV) have become a means of civilization and universalization. The UAV image is gradually replacing aerospace remote sensing data and is widely used in many fields. The limitation that the orthophotos can only be taken from a vertical angle in the past has been broken nowadays by oblique photogrammetry which has wide application prospect in 3D modeling. Aiming to ensure three-no-image (i.e., no camera calibration parameters, no strip information (disordered), and no POS (Position and orientation System) information) in some oblique images, the paper proposes a method of automatic aerial triangulation and 3D reconstruction for the three-no-image. This method is based on the content-based image retrieval method and improved progressive SFM (Structure from Motion) method in computer vision. Firstly, the method retrieves similar images and establishes the network through extracted features. Secondly, the correspondence between the two images is enhanced by matching the images and the tie points are tracked. Thirdly, the 3D point cloud of image is obtained by bundle adjustment. The algorithm improves the accuracy and robustness of reconstruction and makes a great progress in large scale image retrieval and image matching. Finally, , the stability, reliability, and accuracy of the proposed method was tested and validated with three-test experiments by using large scale real oblique images over three test areas. The test-1 area has 1190 images, from the project construction to the final aerial triangulation calculation without control, the total time is 4.3 hours, and the error is 0.4 pixels. The test-2 has 3685 images and no POS is used in experiment. From the project construction to the final aerial triangulation calculation without control, it takes 8 hours and the error is within 0.32 pixels. The two experimental results verified the stability and applicability of the proposed algorithm. The test-3 area has 1346 images, after 5 hours processing, the error of the free network adjustment is within 0.42 pixels, 9 ground control points are used for check points, the error is within 0.16 m in plane and 0.18 m in elevation. The experimental results verified the accuracy and reliability of the proposed algorithm.

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    Accuracy Assessment of Airborne LiDAR Point Cloud Using High Precision DLG as Reference
    Pengjie TAO, Mengxiao SONG, Yansong DUAN
    2019, 21 (4):  608-614.  doi: 10.12082/dqxxkx.2019.180425
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    LiDAR is an active topographic mapping technique for obtaining high precision surface geometric information. In recent years, LiDAR point cloud has been widely used and gradually become a new standard geospatial information product, because of its efficiency, directness and easy availability. Due to its high accuracy, LiDAR point cloud data can be used as georeference data for aerial triangulation of unmanned aerial vehicle (UAV) imagery with sparse ground control points (GCPs) or even without GCP. Because the accuracy of aerial triangulation strongly depends on the accuracy of georeference data itself, so it is of great practical significance to evaluate the accuracy of LiDAR point cloud as georeference data. In this study, we proposed a method for evaluating the accuracy of airborne LiDAR point cloud data using high precision digital line graphic (DLG) as reference data. This method realizes not only the assessment of the vertical accuracy of LiDAR point cloud, but also the reliable assessment of the horizontal accuracy of LiDAR point cloud. Firstly, the vertical accuracy was evaluated by comparing the elevations of the elevation points in DLG with the elevations of the LiDAR points at corresponding positions. Secondly, the facade points of LiDAR buildings were extracted and projected into a horizontal plane, and their distances from the outlines of buildings in DLG were calculated to evaluate the horizontal accuracy of LiDAR point cloud. Due to the existence of a large number of elevation points and building contours in the DLG, the accuracy assessment samples were abundant, and the assessment results could reflect the true accuracy level of LiDAR point cloud. The experiments showed that the horizontal and vertical accuracy of LiDAR point cloud in the test area could reach 7.2 cm and 8.3 cm, respectively, which proved that LiDAR can be used as an effective control data for large scale UAV aerial remote sensing purpose.

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    Progressive Morphological Filtering Method of Dense Matching Point Cloud based on Region Feature Segmentation
    Gang ZHANG, Wenbin LIU, Nan ZHANG
    2019, 21 (4):  615-622.  doi: 10.12082/dqxxkx.2018.0452
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    With the progress of computer vision and RS, dense matching based on remote sensing images has also become one of the important means to obtain high-precision point clouds. Like point clouds of LiDAR, filtering is the fundamental step. Dense matching point cloud is similar with LiDAR point cloud, but have different feature. In this paper, the feature condition is added to the progressive morphological filtering algorithm, point clouds and images are combined into RGB-Depth images, and depth images are semantically segmented according to typical object types, so that point clouds which coordinate correspond with image coordinate are marked and filtered for the first time. Then divide point clouds by grid, then do simply classified according to geometric features, and the improved irregular triangular network of ground points is constructed by filter parameters corresponding to the classification results. Finally, use and intergraded the pre-filtering results and the semantic segmentation results, the regions with similar features are optimized and confirmed by predefined parameter, and the final filtering results are obtained. The results are compared with results of the Cloth Simulated Filtering algorithm. The test result was show that type I error less than 1.98%, type II error less than 2.33% of the progressive morphological filtering algorithm, that algorithm is suitable for higher precision application, especially mixed terrain points cloud filtering.

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    Implementation of Retinex Image Enhancement Algorithm on GPU Platform
    Hao WANG, Hanyu WANG, Mingyu YANG, Yongsen XU
    2019, 21 (4):  623-629.  doi: 10.12082/dqxxkx.2019.180576
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    With the advent of the era of UAV,the real-time requriements for massive data processing are getting higher.Achieve parallel processing of Retinex image enhancement algorithm on the GPU (Graphic Processing Unit) platform, which improves the processing speed of Retinex image enhancement algorithm for processing high resolution digital images.Firstly, by data combine-accessing and memory data interaction technology realize fast access of data, shorten the transmission time of data between different kinds of memory, and improve the efficiency of data access. Then, using kernel instruction optimization and data parallel computing technology, the multi-core programming of Retinex image enhancement algorithm on GPU platform is realized.Finally, the asynchronous execution mode of the host and the device is used to perform parallel calculation of the kernel data while data transmission, and the execution time of the algorithm on the GPU platform is further shortened by the parallel of the task level. With the powerful parallel computing power of the GPU, the processing speed of the Retinex algorithm is greatly improved. For images of different resolutions, the processing speed of the Retinex image enhancement algorithm is tens of times higher than that of the CPU platform. Processing an image with a resolution of 2048×2048 pixels requires only 38.04 ms, and the processing speed of the algorithm is 40 times higher than that of the CPU.

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