Further infrared systems studies for the earth resources program Final report

Design of multispectral scanner for orbital earth resources detectio

Video Stabilization Algorithm from Low Frame Rate Video for Hyperlapse Applications

There are several methods that one can use to visualize image sequences. One such method, called timelapse, is based on synthesizing a video from the image sequence. One sub category of timelapses is the so-called hyperlapse, which is defined as a timelapse with a camera movement over great space. A problem with combining camera movement with speeding up the frame rate per second is that camera shakes appear magnified. One way to minimize this problem is to stabilize the video, using estimated relative camera movement. Such estimates can be obtained using computer vision methods based on epipolar geometry. Choosing how to compensate for camera shakes and calculate a new, more smooth camera path is essential to the video stabilization algorithm. One aim of this thesis is to create such a video stabilization algorithm. Another aim is to examine how performance degrades with decreased frame rate for the input sequence. Along with this thesis we have collected a set of benchmark image sequences. Several different video stabilization algorithms have been developed in the project. These have all been tested on the benchmark data sets and evaluated with promising results.I dagens samhälle är vi alltmer ivriga att dokumentera och dela våra upplevelser och vår vardag med andra genom sociala medier. Ett nytt sätt att göra detta har utvecklats av Narrative som med sin smidiga kamera, vilken kan fästas på dina kläder, erbjuder dig ett verktyg att dokumentera händelser utan att du behöver anstränga dig. Men om man vill presentera bilderna som en video, går det? Det är frågan som har legat bakom vårt examensarbete

Multimedia Forensics

This book is open access. Media forensics has never been more relevant to societal life. Not only media content represents an ever-increasing share of the data traveling on the net and the preferred communications means for most users, it has also become integral part of most innovative applications in the digital information ecosystem that serves various sectors of society, from the entertainment, to journalism, to politics. Undoubtedly, the advances in deep learning and computational imaging contributed significantly to this outcome. The underlying technologies that drive this trend, however, also pose a profound challenge in establishing trust in what we see, hear, and read, and make media content the preferred target of malicious attacks. In this new threat landscape powered by innovative imaging technologies and sophisticated tools, based on autoencoders and generative adversarial networks, this book fills an important gap. It presents a comprehensive review of state-of-the-art forensics capabilities that relate to media attribution, integrity and authenticity verification, and counter forensics. Its content is developed to provide practitioners, researchers, photo and video enthusiasts, and students a holistic view of the field

Multimedia Forensics

This book is open access. Media forensics has never been more relevant to societal life. Not only media content represents an ever-increasing share of the data traveling on the net and the preferred communications means for most users, it has also become integral part of most innovative applications in the digital information ecosystem that serves various sectors of society, from the entertainment, to journalism, to politics. Undoubtedly, the advances in deep learning and computational imaging contributed significantly to this outcome. The underlying technologies that drive this trend, however, also pose a profound challenge in establishing trust in what we see, hear, and read, and make media content the preferred target of malicious attacks. In this new threat landscape powered by innovative imaging technologies and sophisticated tools, based on autoencoders and generative adversarial networks, this book fills an important gap. It presents a comprehensive review of state-of-the-art forensics capabilities that relate to media attribution, integrity and authenticity verification, and counter forensics. Its content is developed to provide practitioners, researchers, photo and video enthusiasts, and students a holistic view of the field

From Grain to Pixel

Film is in a state of rapid change, with the transition from analog to digital profoundly affecting not just filmmaking and distribution, but also the theoretical conceptualization of the medium film and the practice of film archiving. New forms of digital archives are being developed that make use of participatory media to provide a more open form of access than any traditional archive has offered before. Film archives are thus faced with new questions and challenges. From Grain to Pixel attempts to bridge the fields of film archiving and academic research, by addressing the discourse on film ontology and analysing how it affects the role of film archives. Fossati proposes a new theoretization of film archival practice as the starting point for a renewed dialogue between film scholars and film archivists.Het bewegende beeld bevindt zich in een overgangsperiode waarin analoge (fotochemische) film geleidelijk vervangen wordt door digitale film. Deze overgang heeft niet alleen diepgaande invloed op filmproductie en -distributie, maar ook op de manier van archiveren van film en de theoretische conceptualisering van dit medium. Van digitale archieven worden steeds nieuwe vormen ontwikkeld. Deze archieven - digitale filmdatabases en YouTube bijvoorbeeld - maken gebruik van media die participatie van vele gebruikers mogelijk maken en worden zo toegankelijker dan ooit. Ondertussen is er nog onvoldoende dialoog tussen archivarissen en filmwetenschappers. From Grain to Pixel slaat een brug tussen archiveringspraktijken en wetenschappelijk onderzoek dat gebaseerd is op relevante debatten in film- en nieuwe mediastudies. Fossati stelt een nieuwe theorie op voor het archiveren en restaureren van film. Dit biedt mogelijkheden voor een hernieuwde dialoog tussen archivarissen en wetenschappers

VISUAL ATTITUDE PROPAGATION FOR SMALL SATELLITES

As electronics become smaller and more capable, it has become possible to conduct meaningful and sophisticated satellite missions in a small form factor. However, the capability of small satellites and the range of possible applications are limited by the capabilities of several technologies, including attitude determination and control systems. This dissertation evaluates the use of image-based visual attitude propagation as a compliment or alternative to other attitude determination technologies that are suitable for miniature satellites. The concept lies in using miniature cameras to track image features across frames and extracting the underlying rotation. The problem of visual attitude propagation as a small satellite attitude determination system is addressed from several aspects: related work, algorithm design, hardware and performance evaluation, possible applications, and on-orbit experimentation. These areas of consideration reflect the organization of this dissertation. A “stellar gyroscope” is developed, which is a visual star-based attitude propagator that uses relative motion of stars in an imager’s field of view to infer the attitude changes. The device generates spacecraft relative attitude estimates in three degrees of freedom. Algorithms to perform the star detection, correspondence, and attitude propagation are presented. The Random Sample Consensus (RANSAC) approach is applied to the correspondence problem to successfully pair stars across frames while mitigating false-positive and false-negative star detections. This approach provides tolerance to the noise levels expected in using miniature optics and no baffling, and the noise caused by radiation dose on orbit. The hardware design and algorithms are validated using test images of the night sky. The application of the stellar gyroscope as part of a CubeSat attitude determination and control system is described. The stellar gyroscope is used to augment a MEMS gyroscope attitude propagation algorithm to minimize drift in the absence of an absolute attitude sensor. The stellar gyroscope is a technology demonstration experiment on KySat-2, a 1-Unit CubeSat being developed in Kentucky that is in line to launch with the NASA ELaNa CubeSat Launch Initiative. It has also been adopted by industry as a sensor for CubeSat Attitude Determination and Control Systems (ADCS)

Short Wave Infrared Imaging System for Night and Day Long Range Facial Recognition and Surveillance

The capability to detect, observe, and positively identify people at a distance is important to numerous security and defense applications. Traditional solutions for human detection and observation include long-range visible imagers for daytime and thermal infrared imagers for night-time use. Positive identification, through computer face recognition, requires facial imagery that can be repeatably matched to a database of visible spectrum facial mug shots. Nighttime identification at large distances is not possible with visible imagers due to lack of light, or with thermal infrared imagers due to poor correlation with visible facial imagery. An active-SWIR imaging system was developed that is eye-safe, invisible, and capable of producing close-up facial imagery at distances of several hundred meters and full body images to thousands of meters, even in total darkness. The SWIR images correlate well to the visible spectrum allowing for biometric facial recognition and long range target detection either day or night. The process of researching existing technologies, establishing requirements of a suitable system, design process, and hardware implementation will be discussed in great detail. Once the system is assembled, it will be used to acquire data not yet produced by any existing technology. The results will be examined and a discussion made into future work