No description available.

The ultimate goal of the development of aerial photogrammery is to acquire rapidly and accurately the ground measurements. However, traditional photogrammetric technologies, particularly in the continuous digital images stitching technique, is still very limited. In the past, the ground control points were used as the references for the image registration, however, it is very time and resource consuming, as well as human visual capability constraint. Accuracy and efficiency are two key factors which need to be enhanced to meet the practical requirement for aerial imageries stitching. The SIFT (Sale Invariant Feature Transform) algorithm was used in the computer vision to perform feature extraction in good condition. The extracted SIFT features are invariant to image scale, rotation, noise and change in illumination, and it is a robust and abundant feature extraction algorithm. SIFT algorithm extracts feature points from multi-scale space. For a large scale aerial image containing huge amount of image contents, it will spend a lot of time to extract features from imagery. Therefore, this study proposes a new method, called Inter-Grid Down-Sampling (IGDS) method, to reduce the image size and relative amount of image information to improve the computing efficiency. The correspondent extracted features are matched in the adjacent images with additional RANSAC outlier removal procedure to select correct and characteristic feature points. Finally the Hugin-Panorama Photo Stitching software is used to stitch all the continuous photogrammetric images for producing a panorama imagery of all flight lines. The experiment results indicate that sub-pixel accuracy for extracted feature points can be obtained when the down-sampling factor 3 was selected for the IGDS method, and it only needs half of the computing time. Compared to the Nearest-Neighbor Interpolation and Cubic Interpolation methods to reduce the image size, the IGDS method can increase more feature extraction efficiency without scarifying the location accuracy. When threshold value for SIFT was set between 0.4 to 0.6, we can achieve the largest correct matching rate. In addition, the RANSAC outlier removal procedure can effectively select the best matching feature points both in numbers and locations. For image stitching, the Hugin-panorama photo stitching software can effectively be used to match feature points and do geometric correction and color adjustment to obtain a consistent panorama imagery. Finally, the proposed method in this study can derive a low-variant in resolution and measurements significance for a stitching image from continuous aerial images.

Modern large telescopes such as TAO, LSST, TMT and EELT require 0.9m-4m monolithic convex secondary mirrors. The fabrication and testing of these large convex secondary mirrors of astronomical telescopes is getting challenging as the aperture of the mirror is getting bigger. The biggest challenge to fabricate these large convex aspheric mirrors is to measure the surface figure to a few nanometers, while maintaining the testing and fabrication cycle to be efficient to minimize the downtime. For the last a couple of decades there was huge advancement in the metrology and fabrication of large aspheric secondary mirrors. College of Optical Sciences in the University Arizona developed a full fabrication and metrology process with extremely high accuracy and efficiency for manufacturing the large convex secondary mirrors. In this paper modern metrology systems including Swing-Arm Optical Coordinate Measuring System (SOCMM) which is comparable to Interferometry and a Sub-aperture stitching interferometry scalable to a several meters have been presented. Also a Computer Controlled Fabrication Process which produces extremely fine surface figure and finish has been demonstrated. These most recent development has been applied to the fabrication and testing of 0.9m aspheric convex secondary mirror for the Tokyo Atacama Observatory's 6.5m telescope and the result has been presented.

I use found botanical material such as leaves, seedpods, and branches to explore human connection to the physical world. By combining these organic objects with the rich traditions of needlecraft, I bind nature and the human touch. Both tender and ruthless, this intricate stitch work communicates the idea that our relationship with the natural world is both tenuously fragile and infinitely complex. The way I think about and make art mirrors the way I think about my life and how I walk through the world. What I do is about elevating details. It is about noticing cycles and connections. It is about regarding a familiar object in a new way. It’s about seeing things and considering their connection to you, their potential futures and possible pasts. There is a depth and an importance to what is present, and what is absent. Invisible narratives are woven into and around each piece, each interaction. As I gather materials with which to work, I consider what connections might exist between us, or how each object might be related to another. I am a cartographer, drawing and plotting an imaginary map, from one object to the next, intervening with each. These objects naturally fit into categories, which relate to my own experiences, but also to their origins and how they came into my hands. The vertices of experience and the actual life trajectory of an object are what interest me the most; the points at which the object and I intersect.

"Unmanned Aerial Vehicles (UAVs) have been widely used in modern warfare for surveillance, reconnaissance and even attack missions. They can provide valuable battlefield information and accomplish dangerous tasks with minimal risk of loss of lives and personal injuries. However, existing UAV systems are far from perfect to meet all possible situations. One of the most notable situations is the support for individual troops. Besides the incapability to always provide images in desired resolution, currently available systems are either too expensive for large-scale deployment or too heavy and complex for a single solder. Intelligent Portable Aerial Surveillance System (IPASS), sponsored by the Air Force Research Laboratory (AFRL), is aimed at developing a low-cost, light-weight unmanned aerial vehicle that can provide sufficient battlefield intelligence for individual troops. The main contributions of this thesis are two-fold (1) the development and verification of a model-based flight simulation for the aircraft, (2) comparison of image stitching techniques to provide a comprehensive aerial surveillance information from multiple vision. To assist with the design and control of the aircraft, dynamical models are established at different complexity levels. Simulations with these models are implemented in Matlab to study the dynamical characteristics of the aircraft. Aerial images acquired from the three onboard cameras are processed after getting the flying platform built. How a particular image is formed from a camera and the general pipeline of the feature-based image stitching method are first introduced in the thesis. To better satisfy the needs of this application, a homography-based stitching method is studied. This method can greatly reduce computation time with very little compromise in the quality of the panorama, which makes real-time video display of the surroundings on the ground station possible. By implementing both of the methods for image stitching using OpenCV, a quantitative comparison in the performance is accomplished."

Ingeniero Civil Eléctrico / En la actualidad, se han desarrollado los algoritmos de stitching para sintetizar el contenido de múltiples imágenes. Dependiendo del tipo de movimiento descrito por la cámara, existen diversas formas de abordar este problema, ya sea generando una imagen plana o una representación tridimensional de la escena. En particular, secuencias de imágenes capturadas con cambios grandes de la posición de la cámara, presentan un desafío para su aplicación directa. Así, el presente trabajo desarrolla una propuesta de algoritmo que incorpora técnicas del estado del arte para abordar este tipo de secuencias. La propuesta se basa en establecer correspondencias mediante la extracción y calce de descriptores visuales y es implementada en dos fases. En la primera, se explora el uso de transformaciones de homografía para relacionar imágenes, proyectando el contenido a una imagen de referencia. En la segunda fase, se estiman simultáneamente las poses de la cámara y una representación aproximada de la escena, correspondiente a una superficie tridimensional, sobre la que se proyecta el contenido de cada vista. Para evaluar el desarrollo, se definen pruebas que incluyen la medición del error de reproyección promedio y la evaluación visual de las composiciones finales. En los resultados obtenidos para el primer enfoque, se miden desplazamientos promedio de más de 4[px] al proyectar sucesivamente puntos correspondientes hacia la vista de referencia. Luego, en la composición final, se observan muchos sectores mal alineados, ya que las transformaciones obtenidas son válidas en zonas muy acotadas de la imagen, producto de las diferencias de profundidad. Estos resultados llevan a implementar la segunda fase, donde se obtienen reconstrucciones parciales de la escena con un error de reproyección promedio de 0.005[px], con desviación de 0.0018[px]. Así, a pesar de la baja densidad de la nube de puntos, existe una mejora en la apreciación visual del alineamiento en la composición, además de introducir la ventaja de utilizar puntos de vista arbitrarios. Con el trabajo realizado, se logran identificar las limitaciones del registro por homografías sobre las secuencias tratadas. Además, se presenta una propuesta que mejora la alineación del primer enfoque, al lograr combinar las distintas vistas de una secuencia sobre una representación tridimensional aproximada de la escena. Finalmente, se concluye que la propuesta desarrollada otorga una base para solucionar el problema planteado y permite identificar líneas de trabajo futuro, entre las cuales se destaca el buscar obtener una reconstrucción métrica densa de la escena que sintetice la información de todas las vistas en el modelo tridimensional. / Este trabajo ha sido parcialmente financiado por Woodtech S.A. y Red To Green S.A. / 16/08/2022

Automated panorama sequence detection in the imagestream from the Narrative Clip. This is done by using sensor data from the Narrative Clip.

The forest industry needs an up-to-date overview of certain areas of a forest, to either estimate damages after a storm or assess its overall health. Today, the use of unmanned aerial vehicles (UAV) have exploded. Almost anyone can own one and they are very easy to operate. They are often equipped with accurate sensors and cameras that can be used for several productive applications. This paper investigates if a UAV equipped with positional sensors and a high resolution camera can be used for taking aerial photographs and together with a mobile devices create a coherent orthophoto in real- or near real-time. Three different seam stitching algorithms are tested and evaluated based on speed, accuracy and visual appearance. The results of using a DJI Matrice 100 UAV together with an iPad Air is presented both qualitative and quantitative.

No description available.

Laser Speckle Contrast Imaging, or LSCI, is a non-invasive, fast, cheap and easy to use perfusion imaging method which has shown potential in many clinical applications. One problem with the technology however is its limiting field-of-view which results in the physician having to examine and work with multiple images instead of one. In this thesis, a real-time image stitching system was designed with the aim of extending the field of view of LSCI instruments. The system implements a feature-based approach to image registration (SIFT), brute-force matching of features and feather blending. The image transformation is estimated using a statistical methodology (RANSAC) and then validated to improve usability. The evaluation of the system is focused on three key factors: running time of the image stitching algorithm, robustness relative-image pair overlap and usability. The results show that stitching of perfusion images is instantaneous pursuant to human perception for lower resolution images and takes 1.5 to 3.5 seconds for larger resolutions. Stitching is robust given an image-pair overlap of 10% or more, however, temporal noise and sparse environments in perfusion images negatively impacts the systems accuracy and usability. In conclusion, given a contrast-rich region, the system is accurate and easy-to-use such that an untrained user can construct a visually-pleasing panorama that consists of 24 stitched images in approximately 7 minutes.