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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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NASA NTRS1990

Design of optimal correlation filters for hybrid vision systems

Research is underway at the NASA Johnson Space Center on the development of vision systems that recognize objects and estimate their position by processing their images. This is a crucial task in many space applications such as autonomous landing on Mars sites, satellite inspection and repair, and docking of space shuttle and space station. Currently available algorithms and hardware are too slow to be suitable for these tasks. Electronic digital hardware exhibits superior performance in computing and control; however, they take too much time to carry out important signal processing operations such as Fourier transformation of image data and calculation of correlation between two images. Fortunately, because of the inherent parallelism, optical devices can carry out these operations very fast, although they are not quite suitable for computation and control type operations. Hence, investigations are currently being conducted on the development of hybrid vision systems that utilize both optical techniques and digital processing jointly to carry out the object recognition tasks in real time. Algorithms for the design of optimal filters for use in hybrid vision systems were developed. Specifically, an algorithm was developed for the design of real-valued frequency plane correlation filters. Furthermore, research was also conducted on designing correlation filters optimal in the sense of providing maximum signal-to-nose ratio when noise is present in the detectors in the correlation plane. Algorithms were developed for the design of different types of optimal filters: complex filters, real-value filters, phase-only filters, ternary-valued filters, coupled filters. This report presents some of these algorithms in detail along with their derivations.

Rajan, Periasamy K.↗

NASA NTRS1994

Correcting the distortion of images taken with the ultraviolet imaging telescope

The Ultraviolet Imaging Telescope (UIT) cameras include two-stage magnetically focused image intensifiers that introduce small but significant geometrical distortions into the data. These distortions, which create positional offsets as large as 25 arcsec at the field edges, are corrected by the procedure described here to 2-3 arcsec, approximately the resolution of the images. The distortion is measured by comparing and correcting UIT images to digitized Guidestar survey plates of the same fields. Two-dimensional third-order polynomials are used to model the distortion. The models assume that the distortion is an instrumental effect, independent of mission elapsed time and target, and that the effect of distortion is an instrumental effect, independent of mission elapsed time and target, and that the effect of distortion in the center of each field is minimal. The models are used to improve computed astrometric plate solutions and to remove the geometric distortion while transforming the image to a standard north-up, ease-left orientation.

Greason, M. R.↗

NASA NTRS2016

Multi Spectural Flourescence Imager (MSFI)

Multi-Spectural↗

NASA NTRS2016

Multi Spectral Fluorescence Imager (MSFI)

Genetic transformation with in vivo reporter genes for fluorescent proteins can be performed on a variety of organisms to address fundamental biological questions. Model organisms that may utilize an ISS imager include unicellular organisms (Saccharomyces cerevisiae), plants (Arabidopsis thaliana), and invertebrates (Caenorhabditis elegans). The multispectral fluorescence imager (MSFI) will have the capability to accommodate 10 cm x 10 cm Petri plates, various sized multi-well culture plates, and other custom culture containers. Features will include programmable temperature and light cycles, ethylene scrubbing (less than 25 ppb), CO2 control (between 400 ppm and ISS-ambient levels in units of 100 ppm) and sufficient airflow to prevent condensation that would interfere with imaging.

Fluorescence↗

NASA NTRS1992

An IDL-based analysis package for COBE and other skycube-formatted astronomical data

UIMAGE is a data analysis package written in IDL for the Cosmic Background Explorer (COBE) project. COBE has extraordinarily stringent accuracy requirements: 1 percent mid-infrared absolute photometry, 0.01 percent submillimeter absolute spectrometry, and 0.0001 percent submillimeter relative photometry. Thus, many of the transformations and image enhancements common to analysis of large data sets must be done with special care. UIMAGE is unusual in this sense in that it performs as many of its operations as possible on the data in its native format and projection, which in the case of COBE is the quadrilateralized sphereical cube ('skycube'). That is, after reprojecting the data, e.g., onto an Aitoff map, the user who performs an operation such as taking a crosscut or extracting data from a pixel is transparently acting upon the skycube data from which the projection was made, thereby preserving the accuracy of the result. Current plans call for formatting external data bases such as CO maps into the skycube format with a high-accuracy transformation, thereby allowing Guest Investigators to use UIMAGE for direct comparison of the COBE maps with those at other wavelengths from other instruments. It is completely menu-driven so that its use requires no knowledge of IDL. Its functionality includes I/O from the COBE archives, FITS files, and IDL save sets as well as standard analysis operations such as smoothing, reprojection, zooming, statistics of areas, spectral analysis, etc. One of UIMAGE's more advanced and attractive features is its terminal independence. Most of the operations (e.g., menu-item selection or pixel selection) that are driven by the mouse on an X-windows terminal are also available using arrow keys and keyboard entry (e.g., pixel coordinates) on VT200 and Tektronix-class terminals. Even limited grey scales of images are available this way. Obviously, image processing is very limited on this type of terminal, but it is nonetheless surprising how much analysis can be done on that medium. Such flexibility has the virtue of expanding the user community to those who must work remotely on non-image terminals, e.g., via modem.

Ewing, J. A.↗

DOE OSTI2025

Contaminant Investigation and Pre‐Processing Opportunities for Textile‐To‐Textile Recycling

Millions of metric tons of textiles are landfilled or incinerated each year in the United States, with less than 1% of textiles recycled into new clothing or fabrics. To counter this trend, a growing number of companies and researchers are exploring how a circular economy can be applied to support textile‐to‐textile recycling. A significant barrier they face comes down to quickly and efficiently extracting pure feedstock material from post‐consumer garments that feature a mix of natural and synthetic fibers. Textile recyclers prefer pure feedstocks, as working with mixed sources typically means lower throughput, higher risk of equipment failure, and diminished business margins. To facilitate a circular economy for textiles, methods, and technologies are needed that can efficiently separate out materials and contaminants from end‐of‐life textiles to increase the flow of pure feedstocks to recyclers. This paper summarizes findings from interviews with a cross section of textile recyclers and from a review of literature to define basic feedstock requirements. In addition to our qualitative research, we deconstruct a bale of post‐consumer textiles and analyze them using computer‐vision imaging, Fourier transform infrared spectroscopy (FTIR), and machine learning. The resulting data are used to set system‐level design inputs for an automated contaminant removal system to process post‐consumer clothing into appropriate feedstocks for recycling. To set the system's levels for automated real‐time near‐infrared analysis, we identify the minimum percentage of primary material that any single garment in a load of used clothing must contain for the average of the full output stream to meet the target purity levels of recyclers. Here, the envisioned automated system can also address undesirable trace materials that might contaminate the processed stream by using imaging cameras coupled with artificial intelligence to identify sections of clothing for de‐trimming. Proof‐of‐concept machine learning algorithms are evaluated to locate and identify trims or garment areas with hidden contaminant materials. Integrating these methods into automated textile cutting systems can provide a cost‐effective means for increasing feedstock purity from used clothing, which can advance circularity for textiles by helping recyclers to reach production volumes and quality targets that were not possible solely with manual dismantling operations.

Parsons, Ryan [Rochester Institute of Technology, ↗

NASA NTRS1990

Pyramid image codes

All vision systems, both human and machine, transform the spatial image into a coded representation. Particular codes may be optimized for efficiency or to extract useful image features. Researchers explored image codes based on primary visual cortex in man and other primates. Understanding these codes will advance the art in image coding, autonomous vision, and computational human factors. In cortex, imagery is coded by features that vary in size, orientation, and position. Researchers have devised a mathematical model of this transformation, called the Hexagonal oriented Orthogonal quadrature Pyramid (HOP). In a pyramid code, features are segregated by size into layers, with fewer features in the layers devoted to large features. Pyramid schemes provide scale invariance, and are useful for coarse-to-fine searching and for progressive transmission of images. The HOP Pyramid is novel in three respects: (1) it uses a hexagonal pixel lattice, (2) it uses oriented features, and (3) it accurately models most of the prominent aspects of primary visual cortex. The transform uses seven basic features (kernels), which may be regarded as three oriented edges, three oriented bars, and one non-oriented blob. Application of these kernels to non-overlapping seven-pixel neighborhoods yields six oriented, high-pass pyramid layers, and one low-pass (blob) layer.

Watson, Andrew B.↗

NASA NTRS2010

Super Resolution Image Enhancement for a Flash Lidar: Back Projection Method

In this paper a new image processing technique for flash LIDAR data is presented as a potential tool to enable safe and precise spacecraft landings in future robotic or crewed lunar and planetary missions. Flash LIDARs can generate, in real-time, range data that can be interpreted as a 3-dimensional (3-D) image and transformed into a corresponding digital elevation map (DEM). The NASA Autonomous Landing and Hazard Avoidance (ALHAT) project is capitalizing on this new technology by developing, testing and analyzing flash LIDARs to detect hazardous terrain features such as craters, rocks, and slopes during the descent phase of spacecraft landings. Using a flash LIDAR for this application looks very promising, however through theoretical and simulation analysis the ALHAT team has determined that a single frame, or mosaic, of flash LIDAR data may not be sufficient to build a landing site DEM with acceptable spatial resolution, precision, size, or for a mosaic, in time, to meet current system requirements. One way to overcome this potential limitation is by enhancing the flash LIDAR output images. We propose a new super-resolution algorithm applicable to flash LIDAR range data that will create a DEM with sufficient accuracy, precision and size to meet current ALHAT requirements. The performance of our super-resolution algorithm is analyzed by processing data generated during a series of simulation runs by a high fidelity model of a flash LIDAR imaging a high resolution synthetic lunar elevation map. The flash LIDAR model is attached to a simulated spacecraft by a gimbal that points the LIDAR to a target landing site. For each simulation run, a sequence of flash LIDAR frames is recorded and processed as the spacecraft descends toward the landing site. Each run has a different trajectory profile with varying LIDAR look angles of the terrain. We process the output LIDAR frames using our SR algorithm and the results show that the achieved level of accuracy and precision of the SR generated landing site DEM is more than adequate for detecting hazardous terrain features and identifying safe areas.

Bulyshev, Alexander↗

NASA NTRS1993

Image remapping strategies applied as protheses for the visually impaired

Maculopathy and retinitis pigmentosa (rp) are two vision defects which render the afflicted person with impaired ability to read and recognize visual patterns. For some time there has been interest and work on the use of image remapping techniques to provide a visual aid for individuals with these impairments. The basic concept is to remap an image according to some mathematical transformation such that the image is warped around a maculopathic defect (scotoma) or within the rp foveal region of retinal sensitivity. NASA/JSC has been pursuing this research using angle invariant transformations with testing of the resulting remapping using subjects and facilities of the University of Houston, College of Optometry. Testing is facilitated by use of a hardware device, the Programmable Remapper, to provide the remapping of video images. This report presents the results of studies of alternative remapping transformations with the objective of improving subject reading rates and pattern recognition. In particular a form of conformal transformation was developed which provides for a smooth warping of an image around a scotoma. In such a case it is shown that distortion of characters and lines of characters is minimized which should lead to enhanced character recognition. In addition studies were made of alternative transformations which, although not conformal, provide for similar low character distortion remapping. A second, non-conformal transformation was studied for remapping of images to aid rp impairments. In this case a transformation was investigated which allows remapping of a vision field into a circular area representing the foveal retina region. The size and spatial representation of the image are selectable. It is shown that parametric adjustments allow for a wide variation of how a visual field is presented to the sensitive retina. This study also presents some preliminary considerations of how a prosthetic device could be implemented in a practical sense, vis-a-vis, size, weight and portability.

Johnson, Curtis D.↗

DOE OSTI2025

Spectral Performance of Multilayer Amorphous Selenium and Selenium–Tellurium Photodetectors

The ability to robustly and with scalability detect single photons in the visible spectrum with wavelength resolution would transform many imaging applications. Theoretical studies propose an array of carbon nanotubes (CNTs) functionalized with semiconductor quantum dots (QDs) as a physical realization of such photon sensors. In this work, we report approaches to synthesize these CNT-QD nanostructures using DNA as a smart glue to connect CNTs to QDs.

36 MATERIALS SCIENCE↗

DOE OSTI2025

MS-POFT: multiscale phase-orientation guided feature transform for multi-modal image matching

Not Available

Zhang, Zhizheng (ORCID:0009000494711555)↗

DOE OSTI2026

3D reconstruction and neural rendering for adversarial machine learning

While evasion attacks on computer vision systems have been widely studied, creating attacks that remain effective under significant changes in viewpoint continues to be challenging. Traditional approaches often rely on affine transformations of images, but these approaches degrade at larger perspective shifts and often produce unrealistic or ineffective perturbations. Recent methods use differentiable renderers to improve viewpoint robustness, but they typically depend on manually constructed 3D models. We introduce a semi-automated pipeline that generates physically printable and perspective-invariant adversarial patches using only a small set of 2D images. Our method integrates 3D reconstruction, neural rendering, adversarial patch optimization, and an object detection victim model into a unified workflow. We use 2D Gaussian Splatting for high fidelity mesh reconstruction and FlexPara for surface parameterization that produces texture maps suitable for patch editing. Together, these components form a fully differentiable pipeline in PyTorch3D that links texture modification to model outputs, enabling efficient optimization of patches that remain effective across many viewpoints. The complete process, from image capture to patch printing and physical evaluation, can be completed within a few hours. We demonstrate the effectiveness of the resulting patches through attacks on the YOLOv8 object detection model and discuss remaining challenges and opportunities for improving robustness and scalability.

Singhvi, Vivaan [ORNL] (ORCID:0009000586288221)↗

DOE OSTI2025

Topology-imprinting in nonlinear metasurfaces

Flat optical components, or metasurfaces, have transformed optical imaging, data storage, information processing, and biomedical applications by providing unprecedented control over light-matter interactions. These nano-engineered structures enable compact, multidimensional manipulation of light’s amplitude, phase, polarization, and wavefront, producing scalar and vector beams with unique properties such as orbital angular momentum and knotted topologies. This flexibility has potential applications in optical communication and imaging, particularly in complex environments such as atmospheric turbulence and undersea scattering. However, designing metasurfaces for shorter wavelengths, such as visible and ultraviolet light, remains challenging due to fabrication limitations and material absorption. Here, we introduce an innovative concept called topology imprinting using judiciously designed all-dielectric nonlinear optical metasurfaces to replicate desired waveforms at fundamental and harmonic frequencies, opening promising avenues for advanced photonic applications.

42 ENGINEERING↗

DOE OSTI2024

OReole-FM: successes and challenges toward billion-parameter foundation models for high-resolution satellite imagery

While the pretraining of Foundation Models (FMs) for remote sensing (RS) imagery is on the rise, models remain restricted to a few hundred million parameters. Scaling models to billions of parameters has been shown to yield unprecedented benefits including emergent abilities, but requires data scaling and computing resources typically not available outside industry R&D labs. In this work, we pair high-performance computing resources including Frontier supercomputer, America's first exascale system, and high-resolution optical RS data to pretrain billion-scale FMs. Our study assesses performance of different pretrained variants of vision Transformers across image classification, semantic segmentation and object detection benchmarks, which highlight the importance of data scaling for effective model scaling. Moreover, we discuss construction of a novel TIU pretraining dataset, model initialization, with data and pretrained models intended for public release. By discussing technical challenges and details often lacking in the related literature, this work is intended to offer best practices to the geospatial community toward efficient training and benchmarking of larger FMs.

Ambrozio Dias, Philipe↗

NASA NTRS1975

A study to analyze six band multispectral images and fabricate a Fourier transform detector

An automatic Fourier transform diffraction pattern sampling system, used to investigate techniques for forestry classification of six band multispectral aerial photography is presented. Photographs and diagrams of the design, development and fabrication of a hybrid optical-digital Fourier transform detector are shown. The detector was designed around a concentric ring fiber optic array. This array was formed from many optical fibers which were sorted into concentric rings about a single fiber. All the fibers in each ring were collected into a bundle and terminated into a single photodetector. An optical/digital interface unit consisting of a high level multiplexer, and an analog-to-digital amplifier was also constructed and is described.

Shackelford, R. G.↗

NASA NTRS1985

Aerodynamic properties of turbulent combustion fields

Flow fields involving turbulent flames in premixed gases under a variety of conditions are modeled by the use of a numerical technique based on the random vortex method to solve the Navier-Stokes equations and a flame propagation algorithm to trace the motion of the front and implement the Huygens principle, both due to Chorin. A successive over-relaxation hybrid method is applied to solve the Euler equation for flows in an arbitrarily shaped domain. The method of images, conformal transformation, and the integral-equation technique are also used to treat flows in special cases, according to their particular requirements. Salient features of turbulent flame propagation in premixed gases are interpreted by relating them to the aerodynamic properties of the flow field. Included among them is the well-known cellular structure of flames stabilized by bluff bodies, as well as the formation of the characteristic tulip shape of flames propagating in ducts. In its rudimentary form, the mechanism of propagation of a turbulent flame is shown to consist of: (1) rotary motion of eddies at the flame front, (2) self-advancement of the front at an appropriate normal burning speed, and (3) dynamic effects of expansion due to exothermicity of the combustion reaction. An idealized model is used to illustrate these fundamental mechanisms and to investigate basic aerodynamic features of flames in premixed gases. The case of a confined flame stabilized behind a rearward-facing step is given particular care and attention. Solutions are shown to be in satisfactory agreement with experimental results, especially with respect to global properties such as the average velocity profiles and reattachment length.

Hsiao, C. C.↗

NASA NTRS1985

Cloud-drift wind estimates during PGGE

Cloud drift winds constitute an important component of the First Global Atmospheric Research Program Experiment data base. Data was generated by far different centers, using somewhat different procedures. Image data transformation to wind vectors is discussed. Emphasis is placed on the differences between the processing techniques employed in each system. The use of cloud drift data by global data assimulation systems is reviewed, including quality control and relative weighting.

Mcpherson, R. D.↗

NASA NTRS1987

Structural characterization and gas reactions of small metal particles by high resolution in-situ TEM (Transmission Electron Microscopy) and TED (Transmission Electron Diffraction)

The detection and size analysis of small metal particles supported on amorphous substrates becomes increasingly difficult when the particle size approaches that of the phase contrast background structures of the support. An approach of digital image analysis, involving Fourier transformation of the original image, filtering, and image reconstruction was studied with respect to the likelihood of unambiguously detecting particles of less than 1 nm diameter on amorphous substrates from a single electron micrograph.

Heinemann, K.↗