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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Registration of Textured Remote Sensing Images Using Directional Gabor Frames

In this paper we propose to utilize a new concept of discrete directional Gabor frames for automatic image registration. The directional Gabor representations have been shown to provide more accurate feature extraction than directional wavelet transforms for images where texture is the dominant feature. Initial experimental results are presented here which indicate that discrete directional Gabor frames exhibit strong correlations, which indicates that they are likely to improve the existing image registration toolbox.

Image Processing; Pattern Recognition↗
NASA NTRS2018

Planetary Crater Detection and Registration Using Marked Point Processes, Multiple Birth and Death Algorithms, and Region-Based Analysis

Because of the large variety of sensors and spacecraft collecting data, planetary science needs to integrate various multi-sensor and multi-temporal images. These multiple data represent a precious asset, as they allow the study of targets spectral responses and of changes in the surface structure; because of their variety, they also require accurate and robust registration. A new crater detection algorithm, used to extract features that will be integrated in an image registration framework, is presented. A marked point process-based method has been developed to model the spatial distribution of elliptical objects (i.e. the craters) and a birth-death Markov chain Monte Carlo method, coupled with a region-based scheme aiming at computational efficiency, is used to find the optimal configuration fitting the image. The extracted features are exploited, together with a newly defined fitness function based on a modified Hausdorff distance, by an image registration algorithm whose architecture has been designed to minimize the computational time.

Image Processing:Pattern Recognition↗
NASA NTRS2017

Introduction to Remote Sensing Image Registration

For many applications, accurate and fast image registration of large amounts of multi-source data is the first necessary step before subsequent processing and integration. Image registration is defined by several steps and each step can be approached by various methods which all present diverse advantages and drawbacks depending on the type of data, the type of applications, the a priori information known about the data and the type of accuracy that is required. This paper will first present a general overview of remote sensing image registration and then will go over a few specific methods and their applications.

Pattern Recognition↗
NASA NTRS2017

Knowledge Base for Distributed Spacecraft Mission Design Using the Trade-Space Analysis Tool for Constellations (TAT-C)

Opportunities for multi-point measurements, greater revisit frequency, failure robustness, and improved cost effectiveness motivate consideration of Distributed Spacecraft Missions (DSMs) for future Earth science missions. However, careful analysis is required to assess the distributed sensing capabilities of a constellation compared to more mature monolithic spacecraft while also considering other important dimensions such as cost and risk. The large combinatorial DSM design space limits existing mission analysis tools and exploration methods which emphasize monolithic design variables. The Trade-space Analysis Tool for Constellations (TAT-C) under development at Goddard seeks to enumerate and evaluate alternative mission architectures to minimize cost and maximize scientific return for pre-defined goals during pre-phase A analysis.Similar to other model-centric engineering efforts, efficient data management is a significant challenge for DSM mission analysis. In TAT-C, a Knowledge Base (KB) is envisioned as a cumulative central repository of information and meta-information about DSMs. Initial KB concepts store related data for reuse within or across mission analyses; however, over time, the KB is envisioned to be an important layer to coordinate actions of both human analysts and automated design agents to search a large design space for desirable mission alternatives. Preliminary KB research builds on a modern web technology stack to provide the following functionality: 1) storage of trade-space search requests which set requirements and constraints for DSM concepts, 2) storage of analysis results which quantify performance metrics for evaluated DSM concepts, 3) a RESTful application programming interface (API) for scripted access to data from TAT-C modules, 4) web-based graphical user interface (GUI) for manual access to underlying data, and 5) access control and management restrictions relevant to data protection and security. These efforts have culminated in a prototype KB used by the research team during TAT-C development to assess opportunities for future work.

Pattern Recognition↗
NASA NTRS2017

Registration of Textured Remote Sensing Images Using Directional Gabor Frames

In this paper we propose to utilize a new concept of discrete directional Gabor frames for automatic image registration. The directional Gabor representations have been shown to provide more accurate feature extraction than directional wavelet transforms for images where texture is the dominant feature. Initial experimental results are presented here which indicate that discrete directional Gabor frames exhibit strong correlations, which indicates that they are likely to improve the existing image registration toolbox.

Pattern Recognition↗
NASA NTRS2018

Trade-Space Analysis Tool for Designing Constellations (TAT-C)

While there is growing interest in implementing future NASA Earth Science missions as Distributed Spacecraft Missions (DSMs), there are currently no tool to help in the design of DSMs. The objective of our project is to provide a framework that facilitates DSM Pre-Phase A investigations and optimizes DSM designs with respect to a-priori Science goals. Our Trade-space Analysis Tool for Constellations (TAT-C) allows to investigate questions such as: "Which type of constellations should be chosen? How many spacecraft should be included in the constellation? Which design has the best cost/risk value?" This paper provides a description of the TAT-C tool and its components.

Image Processing↗
NASA NTRS2017

Planetary Crater Detection and Registration Using Marked Point Processes, Graph Cut Algorithms, and Wavelet Transforms

This paper addresses the problem of semi-automatic image registration on planetary images. A joint feature-based and area-based approach is proposed. Firstly, the most relevant craters are extracted from the two images to register, and then, registration is performed in two steps. The first step matches the craters extracted from the images based on a generalized Hausdorff distance. In the second step, the mutual information between the two images is maximized to achieve high registration accuracy. Craters are detected by a stochastic-geometry approach based on a marked point process model and of a multiple-birth-and-cut energy minimization algorithm. The experimental validation is carried out with 13 images for the crater extraction stage, and with 20 semi-synthetic pairs of images with ground truth and several images extracted from actual multi-temporal lunar scenes for the registration phase.

Image Processing; Pattern Recognition↗
NASA NTRS1997

Autonomy Enables New Science Missions

The challenge of space flight in NASA's future is to enable smaller, more frequent and intensive space exploration at much lower total cost without substantially decreasing mission reliability, capability, or the scientific return on investment. The most effective way to achieve this goal is to build intelligent capabilities into the spacecraft themselves. Our technological vision for meeting the challenge of returning quality science through limited communication bandwidth will actually put scientists in a more direct link with the spacecraft than they have enjoyed to date. Ultimately, new classes of exploration missions will be enabled.

autonomy↗
DOE OSTI2010

Hybrid optimization schemes for simulation-based problems.

The inclusion of computer simulations in the study and design of complex engineering systems has created a need for efficient approaches to simulation-based optimization. For example, in water resources management problems, optimization problems regularly consist of objective functions and constraints that rely on output from a PDE-based simulator. Various assumptions can be made to simplify either the objective function or the physical system so that gradient-based methods apply, however the incorporation of realistic objection functions can be accomplished given the availability of derivative-free optimization methods. A wide variety of derivative-free methods exist and each method has both advantages and disadvantages. Therefore, to address such problems, we propose a hybrid approach, which allows the combining of beneficial elements of multiple methods in order to more efficiently search the design space. Specifically, in this paper, we illustrate the capabilities of two novel algorithms; one which hybridizes pattern search optimization with Gaussian Process emulation and the other which hybridizes pattern search and a genetic algorithm. We describe the hybrid methods and give some numerical results for a hydrological application which illustrate that the hybrids find an optimal solution under conditions for which traditional optimal search methods fail.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Modeling Spatial Dependencies in High-Resolution Overhead Imagery

Human settlement regions with different physical and socio-economic attributes exhibit unique spatial characteristics that are often illustrated in high-resolution overhead imageries. For example- size, shape and spatial arrangements of man-made structures are key attributes that vary with respect to the socioeconomic profile of the neighborhood. Successfully modeling these attributes is crucial in developing advanced image understanding systems for interpreting complex aerial scenes. In this paper we present three different approaches to model the spatial context in the overhead imagery. First, we show that the frequency domain of the image can be used to model the spatial context [1]. The shape of the spectral energy contours characterize the scene context and can be exploited as global features. Secondly, we explore a discriminative framework based on the Conditional Random Fields (CRF) [2] to model the spatial context in the overhead imagery. The features derived from the edge orientation distribution calculated for a neighborhood and the associated class labels are used as input features to model the spatial context. Our third approach is based on grouping spatially connected pixels based on the low-level edge primitives to form support-regions [3]. The statistical parameters generated from the support-region feature distributions characterize different geospatial neighborhoods. We apply our approaches on high-resolution overhead imageries. We show that proposed approaches characterize the spatial context in overhead imageries.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2011

Learning Scene Categories from High Resolution Satellite Image for Aerial Video Analysis

Automatic scene categorization can benefit various aerial video processing applications. This paper addresses the problem of predicting the scene category from aerial video frames using a prior model learned from satellite imagery. We show that local and global features in the form of line statistics and 2-D power spectrum parameters respectively can characterize the aerial scene well. The line feature statistics and spatial frequency parameters are useful cues to distinguish between different urban scene categories. We learn the scene prediction model from highresolution satellite imagery to test the model on the Columbus Surrogate Unmanned Aerial Vehicle (CSUAV) dataset ollected by high-altitude wide area UAV sensor platform. e compare the proposed features with the popular Scale nvariant Feature Transform (SIFT) features. Our experimental results show that proposed approach outperforms te SIFT model when the training and testing are conducted n disparate data sources.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2010

Hierarchical image segmentation for learning object priors

The proposed segmentation approach naturally combines experience based and image based information. The experience based information is obtained by training a classifier for each object class. For a given test image, the result of each classifier is represented as a probability map. The final segmentation is obtained with a hierarchial image segmentation algorithm that considers both the probability maps and the image features such as color and edge strength. We also utilize image region hierarchy to obtain not only local but also semi-global features as input to the classifiers. Moreover, to get robust probability maps, we take into account the region context information by averaging the probability maps over different levels of the hierarchical segmentation algorithm. The obtained segmentation results are superior to the state-of-the-art supervised image segmentation algorithms.

47 OTHER INSTRUMENTATION↗
DOE OSTI2011

LANL application communication patterns

This brief presentation describes the communication patterns used by a set of unclassified applications developed at Los Alamos National Laboratory: XNobel/XRAGE/RAGE/SAGE, Krak, Sweep3D, and Partisn. It mentions which processes communicate with which other processes, whether the application is typically run in a strong-scaling mode or a weak-scaling mode, what message sizes are commonly used, and how the application's performance changes at scale.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

R&D100 Finalist: Neuromorphic Cyber Microscope

The Neuromorphic Cyber Microscope provides security analysts with unprecedented visibility of their network, computer and storage assets. This processor is the world's first practical implementation of neuromorphic technology to a major computer science mission. Working with Lewis Rhodes Labs, engineers at Sandia National Laboratories have created a device that is orders of magnitude faster at analyzing data to identify cyber-attacks.

97 MATHEMATICS AND COMPUTING↗