Multi Spectral Image Analysis For Improved Space Object Characterization PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Multi Spectral Image Analysis For Improved Space Object Characterization PDF full book. Access full book title Multi Spectral Image Analysis For Improved Space Object Characterization.
| Author | : |
| Publisher | : |
| Total Pages | : 16 |
| Release | : 2008 |
| Genre | : |
| ISBN | : |
Download Multi-Spectral Image Analysis for Improved Space Object Characterization Book in PDF, ePub and Kindle
The Air Force Research Laboratory (AFRL) is studying the application and utility of various groundbased and space-based optical sensors for improving surveillance of space objects in both Low Earth Orbit (LEO) and Geosynchronous Earth Orbit (GEO). At present, ground-based optical and radar sensors provide the bulk of remotely sensed information on satellites and space debris, and will continue to do so into the foreseeable future. However, in recent years, the Space Based Visible (SBV) sensor was used to demonstrate that a synthesis of space-based visible data with ground-based sensor data could provide enhancements to information obtained from any one source in isolation. The incentives for space-based sensing include improved spatial resolution due to the absence of atmospheric effects and cloud cover and increased flexibility for observations. Though ground-based optical sensors can use adaptive optics to somewhat compensate for atmospheric turbulence, cloud cover and absorption are unavoidable. With recent advances in technology, we are in a far better position to consider what might constitute an ideal system to monitor our surroundings in space. This work has begun at the AFRL using detailed optical sensor simulations and analysis techniques to explore the trade space involved in acquiring and processing data from a variety of hypothetical space-based and ground-based sensor systems. In this paper we briefly review the phenomenology and trade space aspects of what might be required in order to use multiple band-passes, sensor characteristics, and observation and illumination geometries to increase our awareness of objects in space.
| Author | : Thomas Blaschke |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 804 |
| Release | : 2008-08-09 |
| Genre | : Science |
| ISBN | : 3540770585 |
Download Object-Based Image Analysis Book in PDF, ePub and Kindle
This book brings together a collection of invited interdisciplinary persp- tives on the recent topic of Object-based Image Analysis (OBIA). Its c- st tent is based on select papers from the 1 OBIA International Conference held in Salzburg in July 2006, and is enriched by several invited chapters. All submissions have passed through a blind peer-review process resulting in what we believe is a timely volume of the highest scientific, theoretical and technical standards. The concept of OBIA first gained widespread interest within the GIScience (Geographic Information Science) community circa 2000, with the advent of the first commercial software for what was then termed ‘obje- oriented image analysis’. However, it is widely agreed that OBIA builds on older segmentation, edge-detection and classification concepts that have been used in remote sensing image analysis for several decades. Nevert- less, its emergence has provided a new critical bridge to spatial concepts applied in multiscale landscape analysis, Geographic Information Systems (GIS) and the synergy between image-objects and their radiometric char- teristics and analyses in Earth Observation data (EO).
| Author | : Saurabh Prasad |
| Publisher | : Springer Nature |
| Total Pages | : 464 |
| Release | : 2020-04-27 |
| Genre | : Computers |
| ISBN | : 3030386171 |
Download Hyperspectral Image Analysis Book in PDF, ePub and Kindle
This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas. The book covers a diverse array of applications of multispectral/hyperspectral imagery in the context of these algorithms, including remote sensing, face recognition and biomedicine. This book would be particularly beneficial to graduate students and researchers who are taking advanced courses in (or are working in) the areas of image analysis, machine learning and remote sensing with multi-channel optical imagery. Researchers and professionals in academia and industry working in areas such as electrical engineering, civil and environmental engineering, geosciences and biomedical image processing, who work with multi-channel optical data will find this book useful.
| Author | : H. Paul Urbach |
| Publisher | : Springer |
| Total Pages | : 274 |
| Release | : 2018-10-05 |
| Genre | : Science |
| ISBN | : 331996707X |
Download 4th International Symposium of Space Optical Instruments and Applications Book in PDF, ePub and Kindle
This book gathers selected and expanded contributions presented at the 4th Symposium on Space Optical Instruments and Applications, which was held in Delft, the Netherlands, on October 16–18, 2017. This conference series is organized by the Sino-Holland Space Optical Instruments Laboratory, a cooperative platform between China and the Netherlands. The symposium focused on key technological problems regarding optical instruments and their applications in a space context. It covered the latest developments, experiments and results on the theory, instrumentation and applications of space optics. The book is split into five main sections: The first covers optical remote sensing system design, the second focuses on advanced optical system design, and the third addresses remote sensor calibration and measurement. Remote sensing data processing and information extraction are then presented, followed by a final section on remote sensing data applications.
| Author | : |
| Publisher | : |
| Total Pages | : 12 |
| Release | : 2009 |
| Genre | : |
| ISBN | : |
Download Space Object Characterization Using Time-Frequency Analysis of Multi-spectral Measurements from the Magdalena Ridge Observatory Book in PDF, ePub and Kindle
The interactions between the surface materials and the body dynamics complicate the characterization of space objects from their optical signatures. One method for decoupling these two effects on the observed signature is to obtain simultaneous measurements using multiple spectral filter bands. The advantage of this approach is that it provides spectral resolution between the filter bands to identify the different materials based on their optical properties as a function of wavelength and temporal resolution between samples to identify the periodic, quasi-periodic, and transient fluctuations characteristic of the object motions, including attitude control, maneuvers, and station-keeping. We have developed algorithms to extract and to analyze light curve data from unresolved resident space objects (RSO) collected at the Magdalena Ridge Observatory (MRO) using the Multi Lens Array (MLA) camera coupled to the 2.4-m telescope. The MLA camera produces 16 spectrally-filtered and temporally synchronous sub-images ranging from 414 nm to 845 nm. We have developed a filter band calibration using a set of stellar observations to remove the atmospheric refraction and absorption effects and differences in the optical paths across the different filter bands using catalogued spectrophotometric data. We apply wavelet analysis to the RSO optical signature light curves to obtain the time-frequency characteristics of the signal for each band. This information allows us to obtain information about the body motions as a function of time. We next attempt to correlate these characteristics across the different MLA filter bands to derive constraints on the types of surface materials.
| Author | : |
| Publisher | : |
| Total Pages | : |
| Release | : 2003 |
| Genre | : |
| ISBN | : |
Download A Framework for Object Characterization and Matching in Multi--and Hyperspectral Imaging Systems Book in PDF, ePub and Kindle
The idea of shape has been a field of scientific study since the time of Galileo. Most shapes that have been studied until now have been those that are 'conceivable' by the human mind. This has restricted the study of shape by the image processing community to the visible range of the spectrum (an otherwise very small range). Perception of shape in the realm of the spectrum outside of the visible range has not received much attention. However with the recent advancement in imaging systems (multi--and hyperspectral) that can capture images over a wide spectral range, it is only natural to expect this field to receive notice by the imaging community. In this work, the idea of 'shape' in the multi--and hyperspectral imaging scenarios is studied and its paradigms explored. Notions of the hyperspectral cube are borrowed from the remote sensing community as a means of representation of this high dimensional data. In this work, edges of two types are used, one that makes use of the vector valued data in the image and another that treats each spectral band individually. The edge-sets are used to extract spatio-spectral shape signatures of objects which are in turn used for extracting canonical views of objects and also to perform classification using three dimensionality reduction techniques, Principal Component Analysis, Independent Component Analysis and Non-negative Matrix Factorization. As an extension to edge-based decompositions, we also use view-based techniques for classification. The results obtained by using a combination of spatial and spectral information are compared with those resulting from conventional single-band techniques, showing considerable improvement. Issues regarding noisy data have been addressed using two approaches -- increasing the dimensionality of the eigensystem and estimating the new eigensystem under noisy conditions using approximations of results using perturbation theory. The former approach gives a measure of the number of basis vectors.
| Author | : Rajeev Ramanath |
| Publisher | : |
| Total Pages | : 139 |
| Release | : 2003 |
| Genre | : |
| ISBN | : |
Download A Framework for Object Characterization and Matching in Multi--and Hyperspectral Imaging Systems Book in PDF, ePub and Kindle
Keywords: Noise Equivalent Dimensions, Perturbation Theory, Eigenviews, Spatio-spectral Signature, Multispectral Imaging, Hyperspectral Imaging, Object Recognition.
| Author | : Prem Chandra Pandey |
| Publisher | : Elsevier |
| Total Pages | : 508 |
| Release | : 2020-08-05 |
| Genre | : Science |
| ISBN | : 0081028954 |
Download Hyperspectral Remote Sensing Book in PDF, ePub and Kindle
Hyperspectral Remote Sensing: Theory and Applications offers the latest information on the techniques, advances and wide-ranging applications of hyperspectral remote sensing, such as forestry, agriculture, water resources, soil and geology, among others. The book also presents hyperspectral data integration with other sources, such as LiDAR, Multi-spectral data, and other remote sensing techniques. Researchers who use this resource will be able to understand and implement the technology and data in their respective fields. As such, it is a valuable reference for researchers and data analysts in remote sensing and Earth Observation fields and those in ecology, agriculture, hydrology and geology. Includes the theory of hyperspectral remote sensing, along with techniques and applications across a variety of disciplines Presents the processing, methods and techniques utilized for hyperspectral remote sensing and in-situ data collection Provides an overview of the state-of-the-art, including algorithms, techniques and case studies
| Author | : Yuhong He |
| Publisher | : CRC Press |
| Total Pages | : 381 |
| Release | : 2018-06-27 |
| Genre | : Technology & Engineering |
| ISBN | : 0429893000 |
Download High Spatial Resolution Remote Sensing Book in PDF, ePub and Kindle
High spatial resolution remote sensing is an area of considerable current interest and builds on developments in object-based image analysis, commercial high-resolution satellite sensors, and UAVs. It captures more details through high and very high resolution images (10 to 100 cm/pixel). This unprecedented level of detail offers the potential extraction of a range of multi-resource management information, such as precision farming, invasive and endangered vegetative species delineation, forest gap sizes and distribution, locations of highly valued habitats, or sub-canopy topographic information. Information extracted in high spatial remote sensing data right after a devastating earthquake can help assess the damage to roads and buildings and aid in emergency planning for contact and evacuation. To effectively utilize information contained in high spatial resolution imagery, High Spatial Resolution Remote Sensing: Data, Analysis, and Applications addresses some key questions: What are the challenges of using new sensors and new platforms? What are the cutting-edge methods for fine-level information extraction from high spatial resolution images? How can high spatial resolution data improve the quantification and characterization of physical-environmental or human patterns and processes? The answers are built in three separate parts: (1) data acquisition and preprocessing, (2) algorithms and techniques, and (3) case studies and applications. They discuss the opportunities and challenges of using new sensors and platforms and high spatial resolution remote sensing data and recent developments with a focus on UAVs. This work addresses the issues related to high spatial image processing and introduces cutting-edge methods, summarizes state-of-the-art high spatial resolution applications, and demonstrates how high spatial resolution remote sensing can support the extraction of detailed information needed in different systems. Using various high spatial resolution data, the third part of this book covers a range of unique applications, from grasslands to wetlands, karst areas, and cherry orchard trees.
| Author | : |
| Publisher | : |
| Total Pages | : 11 |
| Release | : 2008 |
| Genre | : |
| ISBN | : |
Download Space Object Characterization with 16-Visible-Band Measurements at Magdalena Ridge Observatory Book in PDF, ePub and Kindle
Data was collected at the Magdalena Ridge Observatory (MRO) with the Multi Lens Array (MLA) camera coupled to the MRO 2.4 m telescope. MRO is located at 33.985oN, 252.811oE at an altitude of 3193 m, approximately 30 miles West of Socorro, NM. The MRO facilities are intended for both astronomical research and Resident Space Object (RSO) characterization. The purpose of the measurement campaign was to collect both resolved images and unresolved signatures of RSOs in 16 spectral bands, ranging from 414 nm to 845 nm. During the campaign, observations were made over five sessions for the period 21-27 September 2007. During that time we succeeded in observing and collecting data for 18 different calibration stars and 40 different RSOs, mostly those in Low Earth Orbit (LEO). A major objective of the measurement campaign is to collect RSO data that can be used to select spectral bands optimized for estimating surface material composition. The analysis results help determine the nominal spectral differences for typical RSO materials. The paper will discuss the potential of using a multiband camera for RSO identification and characterization.
