This paper presents a method for determining the GPS location of a ground-based object when imaged from a fixed-wing miniature air vehicle (MAV). Using the pixel location of the target in an image, measurements of MAV position and attitude, and camera pose angles, the target is localized in world coordinates. The main contribution of this paper is to present four techniques for reducing the localization error. In particular, we discuss RLS filtering, bias estimation, flight path selection, and wind estimation. The localization method has been implemented and flight tested on BYU's MAV testbed and experimental results are presented demonstrating the localization of a target to within 3 m of its known GPS location.

/pdf/vision-based-target-geo-location-using-a-fixed-wing-39g5dvzwq2.pdf

Vision-based Target Geo-location using a Fixed-wing Miniature Air Vehicle

This paper addresses the development of a vision-based target tracking system for a small unmanned air vehicle. The algorithm performs autonomous tracking of a moving target, while simultaneously estimating GPS coordinates of the target. A low cost off the shelf system is utilized, with a modified radio controlled aircraft airframe, gas engine and servos. Tracking is enabled using a low-cost, miniature pan-tilt gimbal. The control algorithm provides rapid and sustained target acquisition and tracking capability. A target position estimator was designed and shown to provide reasonable targeting accuracy. The impact of target loss events on the control and estimation algorithms is analyzed in detail.

/pdf/vision-based-tracking-and-motion-estimation-for-moving-4s4mh3zhld.pdf

Vision-based tracking and motion estimation for moving targets using small UAVs

A method for real-time mosaic of video flow acquired by a small low-cost unmanned aerial vehicle (UAV) has been presented in this paper. The basic procedures of real-time mosaic are as follows: (1) Each video frame is resampled and orthorectified using a developed mathematical model, which can simultaneously solve the video camera's interior orientation parameters and the exterior orientation parameters of each video frame; (2) each orthorectified video frame is mosaicked at real time. A test field located in Picayune, Mississippi, has been established for testing our method. Sixty-minute video data were collected using the UAV and were processed using the proposed method. The results demonstrated that each video frame can be geo-orthorectified and mosaicked together to produce a 2-D planimetric mapping at near real time. Accuracy of the mosaicked video images (2-D planimetric map) is approximately 1-2 pixels, when compared to 55 checkpoints, which were measured by differential GPS surveying.

Near Real-Time Orthorectification and Mosaic of Small UAV Video Flow for Time-Critical Event Response

This paper presents a survey of georeferenced point clouds. Concentration is, on the one hand, put on features, which originate in the measurement process themselves, and features derived by processing the point cloud. On the other hand, approaches for the processing of georeferenced point clouds are reviewed. This includes the data structures, but also spatial processing concepts. We suggest a categorization of features into levels that reflect the amount of processing. Point clouds are found across many disciplines, which is reflected in the versatility of the literature suggesting specific features. (authors' abstract)

https://www.mdpi.com/2220-9964/2/4/1038/pdf

Georeferenced Point Clouds: A Survey of Features and Point Cloud Management

Multiscale morphological operators are studied extensively in the literature for image processing and feature extraction purposes In this paper, we model a nonlinear regularization method based on multiscale morphology for edge-preserving super resolution (SR) image reconstruction We formulate SR image reconstruction as a deblurring problem and then solve the inverse problem using Bregman iterations The proposed algorithm can suppress inherent noise generated during low-resolution image formation as well as during SR image estimation efficiently Experimental results show the effectiveness of the proposed regularization and reconstruction method for SR image

Super Resolution Image Reconstruction Through Bregman Iteration Using Morphologic Regularization

This paper describes recent work conducted in collaboration with DSTO Australia and Aerosonde to develop video-based geolocation (targeting) and real-time enhancement of ground features observed from a small unmanned air vehicle (UAV) Here a combination of low-cost GPS, video and attitude sensors are used to estimate the object ground position whilst a simple super-resolution technique is used to enhance images of the object of interest The results of two recent trials of the developed algorithms are presented

A video geo-location and image enhancement tool for small unmanned air vehicles (UAVs)

Resistor array infrared projector nonuniformity correction (NUC) is currently limited in fidelity. In the flood
technique a fundamental limitation has been the inevitable presence of Moire fringes. In this paper, an advanced NUC
procedure is described in which the Moire patterns are successfully subtracted, leading to improved levels of residual
nonuniformity. It is shown that, irrespective of the projection technology, the Moire fringes exist at the unit-under-test
image plane where they appear in general as sampling noise. Their control through choice of mapping ratio is
discussed.

Resistor array infrared projector nonuniformity correction: search for performance improvement III

A search is commenced directed towards understanding the fundamental elements that underlie the generation of nonuniformity correction information in dynamic infrared scene projection systems

Search for optimal infrared projector nonuniformity correction procedures

Results from application of the sparse grid nonuniformity correction procedure within the DSTO resistor array Primary Infrared Scene Projection system are reported. In particular, the techniques used to cover the full dynamic range and to combat camera drift are described. The effectiveness of the projector NUC procedure is assessed and discussed in terms of the scope for further improvement.

Emissive infrared projector sparse grid nonuniformity correction

Super-resolution estimates a high-resolution image from a set of observed low-resolution images of the same scene. We formulate the estimation process as a regularized minimization problem and compare its solution, in terms of effectiveness and accuracy, with a fast super-resolution method developed recently in [1]. Results of numerical simulations are presented.

Leszek Swierkowski

Papers

A video geo-location and image enhancement tool for small unmanned air vehicles (UAVs)

Resistor array infrared projector nonuniformity correction: search for performance improvement III

Search for optimal infrared projector nonuniformity correction procedures

Emissive infrared projector sparse grid nonuniformity correction

Search for a computationally efficient image super-resolution algorithm