Results for “image deconvolution” — Page 4

NASA NTRS2012

Constructing a WISE High Resolution Galaxy Atlas

After eight months of continuous observations, the Wide-field Infrared Survey Explorer (WISE) mapped the entire sky at 3.4 micron, 4.6 micron, 12 micron, and 22 micron. We have begun a dedicated WISE High Resolution Galaxy Atlas project to fully characterize large, nearby galaxies and produce a legacy image atlas and source catalog. Here we summarize the deconvolution techniques used to significantly improve the spatial resolution of WISE imaging, specifically designed to study the internal anatomy of nearby galaxies. As a case study, we present results for the galaxy NGC 1566, comparing the WISE enhanced-resolution image processing to that of Spitzer, Galaxy Evolution Explorer, and ground-based imaging. This is the first paper in a two-part series; results for a larger sample of nearby galaxies are presented in the second paper.

Jarrett, T. H.↗

NASA NTRS1977

Research in Solar Physics: Analysis of Skylab/ATM S-056 X-Ray Data

Data obtained by the X-ray event analyzer are described as well as methods used for film calibration. Topics discussed include analyses of the 15 June 1973 flare, oscillations in the solar soft X-ray flux, and deconvolution of X-ray images of the 5 September 1973 flare.

Henze, W., Jr.↗

NASA NTRS1992

Astronomical data analysis software and systems I; Proceedings of the 1st Annual Conference, Tucson, AZ, Nov. 6-8, 1991

Consideration is given to a definition of a distribution format for X-ray data, the Einstein on-line system, the NASA/IPAC extragalactic database, COBE astronomical databases, Cosmic Background Explorer astronomical databases, the ADAM software environment, the Groningen Image Processing System, search for a common data model for astronomical data analysis systems, deconvolution for real and synthetic apertures, pitfalls in image reconstruction, a direct method for spectral and image restoration, and a discription of a Poisson imagery super resolution algorithm. Also discussed are multivariate statistics on HI and IRAS images, a faint object classification using neural networks, a matched filter for improving SNR of radio maps, automated aperture photometry of CCD images, interactive graphics interpreter, the ROSAT extreme ultra-violet sky survey, a quantitative study of optimal extraction, an automated analysis of spectra, applications of synthetic photometry, an algorithm for extra-solar planet system detection and data reduction facilities for the William Herschel telescope.

Worrall, Diana M.↗

DOE OSTI2022

Glass vs. Backsheet: Deconvoluting the Role of Moisture in Power Loss in Silicon Photovoltaics With Correlated Imaging During Accelerated Testing

Not provided.

Energy & Fuels↗

NASA NTRS2010

Improved Phased Array Imaging of a Model Jet

An advanced phased array system, OptiNav Array 48, and a new deconvolution algorithm, TIDY, have been used to make octave band images of supersonic and subsonic jet noise produced by the NASA Glenn Small Hot Jet Acoustic Rig (SHJAR). The results are much more detailed than previous jet noise images. Shock cell structures and the production of screech in an underexpanded supersonic jet are observed directly. Some trends are similar to observations using spherical and elliptic mirrors that partially informed the two-source model of jet noise, but the radial distribution of high frequency noise near the nozzle appears to differ from expectations of this model. The beamforming approach has been validated by agreement between the integrated image results and the conventional microphone data.

Dougherty, Robert P.↗

NASA NTRS1984

Restored methane band images of Uranus and Neptune

Charge-coupled device images of Uranus and Neptune taken in the 8900-A absorption band of methane are presented. The images have been digitally processed by means of nonlinear deconvolution techniques to partially remove the effects of atmospheric seeing. The restored Uranus images show strong limb brightening consistent with previous observations and theoretical models of the planet's atmosphere. The computer-processed images of Neptune show discrete cloud features similar to those reported previously by Smith, Reitsema, and Larson (1979). A time series of the restored Neptune images shows a continuous variation which may be due to the planet's rotation.

Heasley, J. N.↗

NASA NTRS1994

Recovering the fine structures in solar images

Several examples of the capability of the blind iterative deconvolution (BID) technique to recover the real point spread function, when limited a priori information is available about its characteristics. To demonstrate the potential of image post-processing for probing the fine scale and temporal variability of the solar atmosphere, the BID technique is applied to different samples of solar observations from space. The BID technique was originally proposed for correction of the effects of atmospheric turbulence on optical images. The processed images provide a detailed view of the spatial structure of the solar atmosphere at different heights in regions with different large-scale magnetic field structures.

Karovska, Margarita↗

NASA NTRS2000

Deconvolving the Nucleus of Centaurus A Using Chandra PSF Library

Centaurus A (NGC 5128) is a giant early-type galaxy containing the nearest (at 3.5 Mpc) radio-bright Active Galactic Nucleus (AGN). Cen A was observed with the High Resolution Camera (HRC) on the Chandra X-ray Observatory on several occasions since the launch in July 1999. The high-angular resolution (less than 0.5 arcsecond) Chandra/HRC images reveal X ray multi-scale structures in this object with unprecedented detail and clarity, including the bright nucleus believed to be associated with a supermassive black hole. We explored the spatial extent of the Cen A nucleus using deconvolution techniques on the full resolution Chandra images. Model point spread functions (PSFs) were derived from the standard Chandra raytrace PSF library as well as unresolved point sources observed with Chandra. The deconvolved images show that the Cen A nucleus is resolved and asymmetric. We discuss several possible causes of this extended emission and of the asymmetries.

Karovska, Margarita↗

NASA NTRS2004

HiRes: super-resolution for the Spitzer Space Telescope

We present a description of hires, a super-resolution program based upon the Richardson-Lucy algorithm, generalized to the case of redundant coverage, with higher order optical image distortion, implemented for the Sptizer Space Telescope.

image restoration↗

DOE OSTI2022

Colorectal Cancer Metastases in the Liver Establish Immunosuppressive Spatial Networking between Tumor-Associated SPP1 + Macrophages and Fibroblasts

Abstract Purpose: The liver is the most frequent metastatic site for colorectal cancer. Its microenvironment is modified to provide a niche that is conducive for colorectal cancer cell growth. This study focused on characterizing the cellular changes in the metastatic colorectal cancer (mCRC) liver tumor microenvironment (TME). Experimental Design: We analyzed a series of microsatellite stable (MSS) mCRCs to the liver, paired normal liver tissue, and peripheral blood mononuclear cells using single-cell RNA sequencing (scRNA-seq). We validated our findings using multiplexed spatial imaging and bulk gene expression with cell deconvolution. Results: We identified TME-specific SPP1-expressing macrophages with altered metabolism features, foam cell characteristics, and increased activity in extracellular matrix (ECM) organization. SPP1+ macrophages and fibroblasts expressed complementary ligand–receptor pairs with the potential to mutually influence their gene-expression programs. TME lacked dysfunctional CD8 T cells and contained regulatory T cells, indicative of immunosuppression. Spatial imaging validated these cell states in the TME. Moreover, TME macrophages and fibroblasts had close spatial proximity, which is a requirement for intercellular communication and networking. In an independent cohort of mCRCs in the liver, we confirmed the presence of SPP1+ macrophages and fibroblasts using gene-expression data. An increased proportion of TME fibroblasts was associated with the worst prognosis in these patients. Conclusions: We demonstrated that mCRC in the liver is characterized by transcriptional alterations of macrophages in the TME. Intercellular networking between macrophages and fibroblasts supports colorectal cancer growth in the immunosuppressed metastatic niche in the liver. These features can be used to target immune-checkpoint–resistant MSS tumors.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1994

Deep HST imaging of distant weak radio and field galaxies

We present deep Hubble Space Telescope (HST) Wide-Field Camera (WFC) V- and I-band images of three distant weak radio galaxies with z = 0.311-2.390 and seven field galaxies with z = 0.131-0.58. The images were deconvolved with both the Lucy and multiresolution CLEAN methods, which yield a restoring Full Width at Half Maximum (FWHM) of less than or equal to 0.2 sec, (nearly) preserve photons and signal-to-noise ratio at low spatial frequencies, and produce consistent light profiles down to our 2 sigma surface brightness sensitivity limit of V approximately 27.2 and I approximately 25.9 mag/sq arcsec. Multi-component image modeling was used to provide deconvolution-independent estimates of structural parameters for symmetric galaxies. We present 12-band (m(sub 2750) UBVRIgriJHK) photometry for a subset of the galaxies and bootstrap the unknown FOC/48 zero point at 2750 A in three independent ways (yielding m(sub 2750) = 21.34 +/- 0.09 mag for 1.0 e(-)/s). Two radio galaxies with z = 0.311 and 0.528, as well as one field galaxy with z = 0.58, have the colors and spectra of early-type galaxies, and a(exp 1/4)-like light profiles in the HST images. The two at z greater than 0.5 have little or no color gradients in V - I and are likely giant ellipticals, while the z = 0.311 radio galaxy has a dim exponential disk and is likely an S0. Six of the seven field galaxies have light profiles that indicate (small) inner bulges following a(exp 1/4) laws and outer exponential disks, both with little or no color gradients. These are (early-type) spiral galaxies with z = 0.131-0.528. About half have faint companions or bars. One shows lumpy structure, possibly a merger. The compact narrow-line galaxy 53W002 at z = 2.390 has less than or = 30% +/- 10% of its HST V and I flux in the central kiloparsec (due to its weak Active Galactic Nucleus (AGN)). Most of its light (V approximately equal to 23.3) occurs in a symmetric envelope with a regular a(exp 1/4)-like profile of effective radius a approximately equal to 1.1 sec (approximately equal to 12 kpc for H(sub 0) = 50, q(sub 0) = 0.1. Its (HST) V - I color varies at most from approximately 0.3 mag at a approximately equal to 0.2 sec to approximately 1.2 mag at a approximately greater than 0.4 sec, and possibly to approximately greater than 2.2 mag at a approximately greater than 1.2 sec. Together with its I - K color (approximately equal to 2.5 mag for a approximately greater than 1.0 sec-2.0 sec), this is consistent with an aging stellar population approximately 0.3-0.5 Gyr old in the galaxy center (a approx. less than 2 kpc radius), and possibly approximately 0.5-1.0 Gyr old at a approximately greater than 10 kpc radius. While its outer part may thus have started to collapse at z = 2.5-4, its inner part still is aligned with its redshifted Ly(alpha) cloud and its radio axis, possibly caused by star formation associated with the radio jet, or by reflection from its AGN cone.

Windhorst, R. A.↗

DOE OSTI2024

Three Photon Excited Image Scanning Microscopy for in-Depth Super-Resolution Studies of Biological Samples

Multiphoton laser scanning microscopy is a powerful tool for deep imaging of thick biological samples. Image scanning microscopy (ISM) has demonstrated significant improvements in the signal-to-noise ratio in confocal laser scanning microscopy, while at the same time improving upon the effectively attainable resolution. Two-photon excitation (2PE), combined with ISM, has been shown to allow for deep tissue imaging with enhanced resolution compared to 2PE microscopy. Three-photon excitation (3PE) has enabled record imaging depth and contrast for multiphoton imaging, due to the superior suppression of out-of-focus signal generation. In this paper, we demonstrate super-resolution 3PE ISM. This is achieved using a single-photon avalanche detector array, and 1040-nm pulses for 3PE of blue fluorescence. This method enables subdiffraction limited resolution imaging of biological samples stained with blue fluorescent markers, such as mouse myocardial and spinal cord tissues stained with 4 ′ , 6 -diamidino-2-phenylindole. Deconvolution improves the resolving power further and allows for imaging with better than λ / 8 resolution with respect to the 3PE wavelength λ . With the ISM pixel reassignment procedure, we demonstrate a resolution enhancement of ∼ 1.6 laterally, compared to the resolution attained using a photomultiplier tube in a non-descanned detection arrangement, and a factor of ∼ 1.8 enhancement in axial resolution. The experimentally measured three-dimensional point spread function volume is shrunk ∼ 4.4 -fold, which is close to the theoretically expected enhancement. Published by the American Physical Society 2024

47 OTHER INSTRUMENTATION↗

NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗

NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface. In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha-Ray↗

NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗

NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗

NASA NTRS1985

Resolution enhancement of multichannel microwave imagery from the Nimbus-7 SMMR for maritime rainfall analysis

A restoration of the 37, 21, 18, 10.7, and 6.6 GHz satellite imagery from the scanning multichannel microwave radiometer (SMMR) aboard Nimbus-7 to 22.2 km resolution is attempted using a deconvolution method based upon nonlinear programming. The images are deconvolved with and without the aid of prescribed constraints, which force the processed image to abide by partial a priori knowledge of the high-resolution result. The restored microwave imagery may be utilized to examined the distribution of precipitating liquid water in marine rain systems.

Olson, W. S.↗

NASA NTRS1986

Resolution enhancement of multichannel microwave imagery from the Nimbus-7 SMMR for maritime rainfall analysis

A restoration of the 37, 21, 18, 10.7, and 6.6 GHz satellite imagery from the scanning multichannel microwave radiometer (SMMR) aboard Nimbus-7 to 22.2 km resolution is attempted using a deconvolution method based upon nonlinear programming. The images are deconvolved with and without the aid of prescribed constraints, which force the processed image to abide by partial a priori knowledge of the high-resolution result. The restored microwave imagery may be utilized to examine the distribution of precipitating liquid water in marine rain systems.

Olson, William S.↗