Search NASA⌕ Search

SEARCH · Search NASA

Results for “Image Processing”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Identification of an interstellar oxide grain from the Murchison meteorite by ion imaging

We report here the first use of a new ion-imaging system to locate a rare interstellar aluminum oxide grain in a Murchison acid residue. While several types of carbon-rich interstellar grains, including graphite, diamond, SiC, and TiC, have previously been found, isotopically anomalous interstellar oxide grains have proven more elusive. We have developed an ion imaging system which allows us to map the isotopic composition of large numbers of grains relatively quickly and is, thus, ideally suited to search for isotopically exotic subsets of grains. The system consists of a PHOTOMETRICS CCD camera coupled to the microchannel plate/fluorescent screen of the WU modified CAMECA IMS-3F ion microprobe. Isotopic images of the sample surface are focused on the CCD and digitized. Subsequent image processing identifies individual grains in the images and determines isotopic ratios for each. For the present work, we have imaged in O-16 and O-18; negligible contributions of (17)OH(-) and (16)OH2(-) signals to the O-18 signal allow the use of low mass resolution, simplifying the measurements. Repeated imaging runs on terrestrial corundum particles showed that the system measures isotopic ratios reproducibly to about +/- 40%. Each imaging run took about six minutes to complete, and for this study there were on average 5-15 grains in each image. We have conducted imaging searches in 2-4 micron size separates of both Orgueil and Murchison.

Nittler, L. R.↗
NASA NTRS1995

Exploring the Environment and the Astronomy Village: NASA Classroom of the Future

Astronomy Village: Investigating the Universe is a CD-ROM based multimedia program that provides teachers and students with ten complete investigations in astronomy intended to complement and extend the science curriculum in 9th and 10th grade classes. Students, in teams of three, use the Astronomy Village software to conduct investigations in astronomy and lear about the nature of scientific inquiry. The Astronomy Village's interface is based on the village like appearence of major observatories on mountain tops. Tools available to students include an image processing program, a document reader, an image browser, a telecommunications program for accessing the world wide web, and various simulation programs. The simulation programs include a star life cycle simulator, an orbital simulator, and a 3-D star simulator. Other resources available on this CD for the student research teams include: digitized video clips, images from the Hubble Space Telescope and other instruments; audio clips of astronomers discussing their work; computer animation and graphics; and full text documents such as book chapters, NASA publications, and articles from astronomy journals and magazines.

Myers, Bob↗
NASA NTRS2004

Synchronized Electronic Shutter System and Method for Thermal Nondestructive Evaluation

The invention is a synchronized electronic shutter system (SESS) and method for same side and through transmission thermal analysis and inspection of a material for finding defects, corrosion, disbond defects, integrity of a weld and determination of paint thickness. The system comprises an infrared detector that acquires background images of the sample. A shutter then covers the detector and lamps rapidly heat the sample above ambient temperature. Shutters cover all lamps at the same time the shutter over the infrared detector is opened. The infrared detector acquires a series of temperature images over time radiated from the sample a s the sample cools down. After collecting a series of temperature images taken by the SESS, a processed image is developed using one of the group comprising time derivative calculation, temperature normalization data reduction routine, thermal diffusivity curve fitting and averaging the series of temperature images.

Joseph N Zalameda↗
DOE OSTI2023

Summary report of the 4th IAEA Technical Meeting on Fusion Data Processing, Validation and Analysis (FDPVA)

The objective of the Fourth Technical Meeting on Fusion Data Processing, Validation and Analysis was to provide a platform during which a set of topics relevant to fusion data processing, validation and analysis are discussed with the view of extrapolating needs to next step fusion devices such as ITER. The validation and analysis of experimental data obtained from diagnostics used to characterize fusion plasmas are crucial for a knowledge-based understanding of the physical processes governing the dynamics of these plasmas. This paper presents the recent progress and achievements in the domain of plasma diagnostics and synthetic diagnostics data analysis (including image processing, regression analysis, inverse problems, deep learning, machine learning, big data and physics-based models for control) reported at the meeting. The progress in these areas highlight trends observed in current major fusion confinement devices. A special focus is dedicated on data analysis requirements for ITER and DEMO with a particular attention paid to artificial intelligence for automatization and improving reliability of control processes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1995

Programmable Iterative Optical Image And Data Processing

Proposed method of iterative optical image and data processing overcomes limitations imposed by loss of optical power after repeated passes through many optical elements - especially, beam splitters. Involves selective, timed combination of optical wavefront phase conjugation and amplification to regenerate images in real time to compensate for losses in optical iteration loops; timing such that amplification turned on to regenerate desired image, then turned off so as not to regenerate other, undesired images or spurious light propagating through loops from unwanted reflections.

Jackson, Deborah J.↗
DOE OSTI2023

Laser-Induced Fluorescence for Monitoring Environmental Contamination and Stress in the Moss Thuidium plicatile

The ability to detect, measure, and locate the source of contaminants, especially heavy metals and radionuclides, is of ongoing interest. A common tool for contaminant identification and bioremediation is vegetation that can accumulate and indicate recent and historic pollution. However, large-scale sampling can be costly and labor-intensive. Hence, non-invasive in-situ techniques such as laser-induced fluorescence (LIF) are becoming useful and effective ways to observe the health of plants through the excitation of organic molecules, e.g., chlorophyll. The technique presented utilizes images collected of LIF in moss to identify different metals and environmental stressors. Analysis through image processing of LIF response was key to identifying Cu, Zn, Pb, and a mixture of the metals at nmol/cm 2 levels. Specifically, the RGB values from each image were used to create density histograms of each color channel’s relative pixel abundance at each decimal code value. These histograms were then used to compare color shifts linked to the successful identification of contaminated moss samples. Photoperiod and extraneous environmental stressors had minimal impact on the histogram color shift compared to metals and presented with a response that differentiated them from metal contamination.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1984

Improved Gamma-and X-Ray Pinhole Camera

Electronic additions increase image quality. Digital image-processing equipment electronically performs functions of S1 and D2 improving resolution and adding capability for image storage and further processing. System useful in nuclear medicine or radioisotope imaging, tomography and nuclear industry.

Yin, L. I.↗
DOE OSTI2020

Enabling Highly Efficient Capsule Networks Processing Through A PIM-Based Architecture Design

In recent years, the CNNs have achieved great successes in the image processing tasks, e.g., image recognition and object detection. Unfortunately, traditional CNN's classication is found to be easily misled by increasingly complex image features due to the usage of pooling operations, hence unable to preserve accurate position and pose information of the objects. To address this challenge, a novel neural network structure called Capsule Network has been proposed, which introduces equivariance through capsules to signicantly enhance the learning ability for image segmentation and object detection. Due to its requirement of performing a high volume of matrix operations, CapsNets have been generally accelerated on modern GPU platforms that provide highly optimized software library for common deep learning tasks. However, based on our performance characterization on modern GPUs, CapsNets exhibit low effciency due to the special program and execution features of their routing procedure, including massive unshareable intermediate variables and intensive syn- chronizations, which are very dicult to optimize at software level. To address these challenges, we propose a hybrid computing architecture design named PIM-CapsNet. It preserves GPU's on-chip computing capability for accelerating CNN types of layers in CapsNet, while pipelining with an off-chip in-memory acceleration solution that effectively tackles routing procedure's ineffciency by leveraging the processing-in-memory capability of today's 3D stacked memory. Using routing procedure's inherent parallellization feature, our design enables hierarchical improvements on CapsNet inference effciency through minimizing data movement and maximizing parallel processing in memory. Evaluation results demonstrate that our proposed design can achieve substantial improvement on both performance and energy savings for CapsNet inference, with almost zero accuracy loss. The results also suggest good performance scalability in optimizing the routing procedure with increasing network size.

Zhang, Xingyao↗
NASA NTRS2018

Two and Three Dimensional near Infrared Subcutaneous Structure Imager Using Real Time Nonlinear Video Processing

An imager is provided for viewing subcutaneous structures. In an embodiment of the invention, the imager includes a camera configured to generate a video frame, and an adaptive nonlinear processor. The adaptive nonlinear processor is configured to adjust a signal of the video frame below a first threshold to a maximum dark level and to adjust the signal of the video frame above a second threshold to a maximum light level. The imager further includes a display, configured to display the processed video frame.

Krasowski, Michael J↗
DOE OSTI2024

Skipper-in-CMOS: Nondestructive Readout With Subelectron Noise Performance for Pixel Detectors

The Skipper-in-CMOS image sensor integrates the nondestructive readout capability of skipper charge coupled devices (Skipper-CCDs) with the high conversion gain of a pinned photodiode (PPD) in a CMOS imaging process while taking advantage of in-pixel signal processing. This allows both single photon counting as well as high frame rate readout through highly parallel processing. The first results obtained from a ${15} \times {15}~\mu $ m2 pixel cell of a Skipper-in-CMOS sensor fabricated in Tower Semiconductor’s commercial 180-nm CMOS image sensor process are presented. Measurements confirm the expected reduction of the readout noise with the number of samples down to deep subelectron noise of $0.15\text {e}^ - $ , demonstrating the charge transfer operation from the PPD and the single photon counting operation when the sensor is exposed to light. This article also discusses new testing strategies employed for its operation and characterization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2001

Machine vision guided sensor positioning system for leaf temperature assessment

A sensor positioning system was developed for monitoring plants' well-being using a non-contact sensor. Image processing algorithms were developed to identify a target region on a plant leaf. A novel algorithm to recover view depth was developed by using a camera equipped with a computer-controlled zoom lens. The methodology has improved depth recovery resolution over a conventional monocular imaging technique. An algorithm was also developed to find a maximum enclosed circle on a leaf surface so the conical field-of-view of an infrared temperature sensor could be filled by the target without peripheral noise. The center of the enclosed circle and the estimated depth were used to define the sensor 3-D location for accurate plant temperature measurement.

NASA Discipline Life Support Systems↗
NASA NTRS1989

Measuring Airflow With Digital Holographic Interferometry

Digital image-processing system assists in analysis of holographic interferometric images of flow about airfoil. Operating semiautomatically, identifies, counts, and labels interference fringes, then processes distances between fringes into distribution of pressure on surface of airfoil. Yields data on pressure faster than manual image-analyses techniques, and data compares favorably with those obtained by manual analysis and by probe measurements of pressure. Uses computer programs evaluating interferograms along straight or curved lines represented by polygon segments. User prompted for such inputs as reference points and fringe number. Digitizes holographic interferograms of flow and processes them into data of pressure or other properties of flow.

Torres, Francisco J.↗
DOE OSTI2023

Generalized Quantum Convolution for Multidimensional Data

The convolution operation plays a vital role in a wide range of critical algorithms across various domains, such as digital image processing, convolutional neural networks, and quantum machine learning. In existing implementations, particularly in quantum neural networks, convolution operations are usually approximated by the application of filters with data strides that are equal to the filter window sizes. One challenge with these implementations is preserving the spatial and temporal localities of the input features, specifically for data with higher dimensions. In addition, the deep circuits required to perform quantum convolution with a unity stride, especially for multidimensional data, increase the risk of violating decoherence constraints. In this work, we propose depth-optimized circuits for performing generalized multidimensional quantum convolution operations with unity stride targeting applications that process data with high dimensions, such as hyperspectral imagery and remote sensing. We experimentally evaluate and demonstrate the applicability of the proposed techniques by using real-world, high-resolution, multidimensional image data on a state-of-the-art quantum simulator from IBM Quantum.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1972

Review of coherent optical data processing

The fundamental features of coherent optical data processing systems are reviewed for potential application to image processing. The application of optical spatial filtering to image mapping and cloud motion is discussed.

Vanderlugt, A.↗
NASA NTRSDate not supplied

Unlocking the Mysteries of the Moon’s Shadowed Regions

The Moon poles host large quantities of water-ice deposits in the permanently shadowed regions (PSRs), which are vital for enabling sustainable human space exploration, making these regions high-priority targets for upcoming Artemis missions [1]. Unfortunately, today, the best available orbital lunar imagery [2, 3] lacks the meter-scale resolution and signal needed to understand the geomorphology and trafficability of PSRs, complicating the planning and execution of future missions seeking to explore PSRs. We have developed an image enhancement tool called HORUS (Hyper-effective nOise Removal Unet Software) [4, 5], designed to enhance LRO Narrow-Angle Camera (NAC) optical low-light imagery of permanently shadowed regions by effectively removing the CCD-related, photon, and other residual noises that corrupt the images. The tool is composed of two deep learning neural networks trained on environmental metadata and real and synthetic imagery, the latter generated by a physical noise model (LROC). We demonstrated that HORUS effectively produces low-noise, high-resolution images (~1.5m/px), achieving a 5 to 10x improvement over existing long-exposure images of PSRs. HORUS allows scientists and engineers to identify geomorphic features (e.g., craters and boulders) in shadowed regions as small as 3 meters across as well as to peek inside of small shadowed regions, for the first time. The tool was deployed and thoroughly validated for NASA's VIPER mission [6], where it was applied to 20 candidate target regions across the lunar South Pole. Additionally, we conducted different approaches to validate the resulting HORUS-processed images. With HORUS denoised images, VIPER scientists can increase their confidence on what surface features (previously unseen) exist in the shadowed regions, helping them plan rover traverses more safely and efficiently (e.g., Fig. 1) In this manuscript, we will describe how VIPER scientists are utilizing HORUS denoised images to extract new information from the terrain and increase their confidence in what surface features exist in the shadowed regions. In combination with other high-resolution images and digital elevation maps, HORUS images are helping the team analyze potential lading and science sites, as well as planning traverses more safely and efficiently (e.g., Fig. 1). Additionally, we will describe how HORUS tool unlocks a broad range of scientific and exploration applications to other Artemis and CPLS missions to the lunar poles, including (but not limited to) geomorphic analysis, change detection, surface hazard detection, and terrain relative navigation.

artificial intelligence↗
NASA NTRS1994

Raster Metafile And Raster Metafile Translator Programs

Raster Metafile (RM) computer program is generic raster-image-format program, and Raster Metafile Translator (RMT) program is assortment of software tools for processing images prepared in this format. Processing includes reading, writing, and displaying RM images. Such other image-manipulation features as minimal compositing operator and resizing option available under RMT command structure. RMT written in FORTRAN 77 and C language.

Randall, Donald P.↗