Results for “Image reconstruction” — Page 18

NASA NTRS2001

Matching Images to Models: Camera Calibration for 3-D Surface Reconstruction

In a previous paper we described a system which recursively recovers a super-resolved three dimensional surface model from a set of images of the surface. In that paper we assumed that the camera calibration for each image was known. In this paper we solve two problems. Firstly, if an estimate of the surface is already known, the problem is to calibrate a new image relative to the existing surface model. Secondly, if no surface estimate is available, the relative camera calibration between the images in the set must be estimated. This will allow an initial surface model to be estimated. Results of both types of estimation are given.

Morris, Robin D.↗

NASA NTRS2001

Left ventricular endocardial surface detection based on real-time 3D echocardiographic data

OBJECTIVE: A new computerized semi-automatic method for left ventricular (LV) chamber segmentation is presented. METHODS: The LV is imaged by real-time three-dimensional echocardiography (RT3DE). The surface detection model, based on level set techniques, is applied to RT3DE data for image analysis. The modified level set partial differential equation we use is solved by applying numerical methods for conservation laws. The initial conditions are manually established on some slices of the entire volume. The solution obtained for each slice is a contour line corresponding with the boundary between LV cavity and LV endocardium. RESULTS: The mathematical model has been applied to sequences of frames of human hearts (volume range: 34-109 ml) imaged by 2D and reconstructed off-line and RT3DE data. Volume estimation obtained by this new semi-automatic method shows an excellent correlation with those obtained by manual tracing (r = 0.992). Dynamic change of LV volume during the cardiac cycle is also obtained. CONCLUSION: The volume estimation method is accurate; edge based segmentation, image completion and volume reconstruction can be accomplished. The visualization technique also allows to navigate into the reconstructed volume and to display any section of the volume.

Non-NASA Center↗

NASA NTRS1991

Reconstruction of the Hubble Space Telescope mirror figure from out-of-focus stellar images

Both the amplitude and the phase of the incoming wave front viewed from the focal plane are reconstructed from the illumination recorded in defocused stellar images taken in flight by the HST. The reconstructed wavefront surface shows very little aberration. Compared to geometrical optics methods, the technique produces high spatial resolution wavefront maps with images taken closer to the telescope's focal plane. For the HST, the quality of the wavefront reconstruction is limited by the telescope jitter. The technique cannot be applied to ground-based telescopes at optical wavelength where the image is heavily blurred by the atmosphere. It is argued to be promising as a diagnostic tool for optical telescopes in space.

Roddier, C.↗

NASA NTRS1973

Heterodyne readout for read-write holographic memories

A heterodyne readout technique for read-write holographic memory systems that reconstruct a virtual image wavefront is described and demonstrated. The conventionally recorded hologram is illuminated simultaneously with a suitable combination of temporally modulated reference and modified object waves for readout. Best performance is obtained for temporal phase modulation. The coupling of the illuminating wavefronts by the hologram is analyzed.

Mezrich, R. S.↗

NASA NTRS1975

A statistical technique for processing radio interferometer data

The output of a radio interferometer is the Fourier transform of the object under investigation. Due to the limited coverage of the Fourier plane, the reconstruction of the image of the source is blurred by the beam of the synthesized array. A maximum-likelihood processing technique is described which uses the statistical properties of the received noise-like signals. This technique has been used extensively in the processing of large-aperture seismic arrays. This inversion method results in a synthesized beam that is more uniform, has lower sidelobes, and higher resolution than the normal Fourier transform methods. The maximum-likelihood method algorithm was applied successfully to very long baseline and short baseline interferometric data.

Papadopoulos, G. D.↗

NASA NTRS1976

Charge coupled device integration-time coding for detection of images moving with unknown velocities

Existing techniques for the detection of a moving low light level image by a CCD array have required velocity synchronism between the image and the photogenerated charges. This was necessary to prevent blurring during the long duration of charge integration. A new detection scheme is described which causes the image to be convolved with a clock modulation signal as the photocharges are collected. The charge accumulating from each image point will now be spread over many photoelements due to the absence of velocity synchronism, but the output is not blurred in the usual sense. Instead the charge is distributed through the array in a controlled way so that the image can be reconstructed.

White, J. M.↗

NASA NTRS1976

Mapping of lunar surface from side-looking orbital radar images

Side-looking spacecraft radar imagery has thus far been produced only from an orbit around the moon. This was a part of the Apollo Lunar Sounder Experiment (ALSE) of the Apollo 17 mission in December 1972. This paper reports results of a radargrammetric evaluation of overlapping Apollo 17 synthetic-aperture radar images (wavelength 2 m). The potential to map from single images and to reconstruct three-dimensional stereoscopic models is studied. The relative height accuracy achieved is about + or - 100 m and is thus competitive with that obtained with the vidicon camera presently used for planetary exploration.

Leberl, F.↗

NASA NTRS1984

An approach for automated analysis of particle holograms

A simple method for analyzing droplet holograms is proposed that is readily adaptable to automation using modern image digitizers and analyzers for determination of the number, location, and size distributions of spherical or nearly spherical droplets. The method determines these parameters by finding the spatial location of best focus of the droplet images. With this location known, the particle size may be determined by direct measurement of image area in the focal plane. Particle velocity and trajectory may be determined by comparison of image locations at different instants in time. The method is tested by analyzing digitized images from a reconstructed in-line hologram, and the results show that the method is more accurate than a time-consuming plane-by-plane search for sharpest focus.

Stanton, A. C.↗

NASA NTRS1989

Machine parts recognition using a trinary associative memory

The convergence mechanism of vectors in Hopfield's neural network in relation to recognition of partially known patterns is studied in terms of both inner products and Hamming distance. It has been shown that Hamming distance should not always be used in determining the convergence of vectors. Instead, inner product weighting coefficients play a more dominant role in certain data representations for determining the convergence mechanism. A trinary neuron representation for associative memory is found to be more effective for associative recall. Applications of the trinary associative memory to reconstruct machine part images that are partially missing are demonstrated by means of computer simulation as examples of the usefulness of this approach.

Awwal, Abdul Ahad S.↗

NASA NTRS1989

Image gathering and restoration - Information and visual quality

A method is investigated for optimizing the end-to-end performance of image gathering and restoration for visual quality. To achieve this objective, one must inevitably confront the problems that the visual quality of restored images depends on perceptual rather than mathematical considerations and that these considerations vary with the target, the application, and the observer. The method adopted in this paper is to optimize image gathering informationally and to restore images interactively to obtain the visually preferred trade-off among fidelity resolution, sharpness, and clarity. The results demonstrate that this method leads to significant improvements in the visual quality obtained by the traditional digital processing methods. These traditional methods allow a significant loss of visual quality to occur because they treat the design of the image-gathering system and the formulation of the image-restoration algorithm as two separate tasks and fail to account for the transformations between the continuous and the discrete representations in image gathering and reconstruction.

Mccormick, Judith A.↗

NASA NTRS1989

Mars Rover and Sample Return Mission design

The current reference Mars Rover and Sample Return mission is described. Technical issues are outlined, including high-resolution image acquisition and reconstruction, approach navigation, ground and flight systems operational complexity, rover autonomy, autonomous rendezvous and docking in Mars orbit, aerocapture and aeromaneuver, estimating the probability of mission success, and end-to-end information system design. Focus is placed on lander hazard identification and avoidance, pinpoint landing guidance and control, Mars ascent vehicle guidance and control, planetary protection and quarantine, sample acquisition and preservation, project management and control, systems requirements and interface control, and costing. In addition, program issues such as international participation, fiscal constraints, and launch-vehicle availability are considered.

Kwok, Johnny H.↗

NASA NTRS1994

Spectral eclipse mapping of the accretion disk in the nova-like variable UX Ursae Majoris

We analyze narrow-band eclipse light curves of the nova-like cataclysmic variable UX UMa, obtained from low-resolution spectra spanning lambda lambda 3600-9800 A . The light curves for narrow bands in the continuum as well as those for individual spectral lines are treated independently, and are used to construct images of the accretion disk's brightness distribution using the maximum-entropy eclipse-mapping technique. Particular attention is paid to the propagation of statistical uncertainties in the data and to how the analysis may introduce systematic errors in the final result. From the many narrrow band images we have reconstructed the spectra from isolated parts of the accretion disk. These spectra reveal that the inner disk radiates a continuum spectrum which peaks in the near UV and has the hydrogen Balmer lines in absorption (with the exception of H-alpha), whereas the outer disk is much fainter, has a much redder spectrum, and has Balmer emission lines. Our analysis reveals the presence of an uneclipsed component of the total light, whose spectrum is very red and has Balmer lines in emission. This unexpected feature of the eclipse mapping technique offers a new tool for an independent assessment of the secondary star's spectrum in eclipsing cataclysmic variables.

Rutten, R. G. M.↗

NASA NTRS2000

Computer Tomography Analysis of Fastrac Composite Thrust Chamber Assemblies

Computed tomography (CT) inspection has been integrated into the production process for NASA's Fastrac composite thrust chamber assemblies (TCAs). CT has been proven to be uniquely qualified to detect the known critical flaw for these nozzles, liner cracks that are adjacent to debonds between the liner and overwrap. CT is also being used as a process monitoring tool through analysis of low density indications in the nozzle overwraps. 3d reconstruction of CT images to produce models of flawed areas is being used to give program engineers better insight into the location and nature of nozzle flaws.

Beshears, Ronald D.↗

NASA NTRS2010

Advances in HgCdTe APDs and LADAR Receivers

Raytheon is developing NIR sensor chip assemblies (SCAs) for scanning and staring 3D LADAR systems. High sensitivity is obtained by integrating high performance detectors with gain i.e. APDs with very low noise Readout Integrated Circuits. Unique aspects of these designs include: independent acquisition (non-gated) of pulse returns, multiple pulse returns with both time and intensity reported to enable full 3D reconstruction of the image. Recent breakthrough in device design has resulted in HgCdTe APDs operating at 300K with essentially no excess noise to gains in excess of 100, low NEP <1nW and GHz bandwidths and have demonstrated linear mode photon counting. SCAs utilizing these high performance APDs have been integrated and demonstrated excellent spatial and range resolution enabling detailed 3D imagery both at short range and long ranges. In this presentation we will review progress in high resolution scanning, staring and ultra-high sensitivity photon counting LADAR sensors.

Bailey, Steven↗

NASA NTRS2012

Advances in LADAR Components and Subsystems at Raytheon

Raytheon is developing NIR sensor chip assemblies (SCAs) for scanning and staring 3D LADAR systems. High sensitivity is obtained by integrating high performance detectors with gain, i.e., APDs with very low noise Readout Integrated Circuits (ROICs). Unique aspects of these designs include: independent acquisition (non-gated) of pulse returns, multiple pulse returns with both time and intensity reported to enable full 3D reconstruction of the image. Recent breakthrough in device design has resulted in HgCdTe APDs operating at 300K with essentially no excess noise to gains in excess of 100, low NEP <1nW and GHz bandwidths and have demonstrated linear mode photon counting. SCAs utilizing these high performance APDs have been integrated and demonstrated excellent spatial and range resolution enabling detailed 3D imagery both at short range and long ranges. In the following we will review progress in real-time 3D LADAR imaging receiver products in three areas: (1) scanning 256 x 4 configuration for the Multi-Mode Sensor Seeker (MMSS) program and (2) staring 256 x 256 configuration for the Autonomous Landing and Hazard Avoidance Technology (ALHAT) lunar landing mission and (3) Photon-Counting SCAs which have demonstrated a dramatic reduction in dark count rate due to improved design, operation and processing.

Jack, Michael↗

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↗