Search NASA⌕ Search

SEARCH · Search NASA

Results for “Image restoration”

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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

Optimum constrained image restoration filters

The filter was developed in Hilbert space by minimizing the radius of gyration of the overall or composite system point-spread function subject to constraints on the radius of gyration of the restoration filter point-spread function, the total noise power in the restored image, and the shape of the composite system frequency spectrum. An iterative technique is introduced which alters the shape of the optimum composite system point-spread function, producing a suboptimal restoration filter which suppresses undesirable secondary oscillations. Finally this technique is applied to multispectral scanner data obtained from the Earth Resources Technology Satellite to provide resolution enhancement. An experimental approach to the problems involving estimation of the effective scanner aperture and matching the ERTS data to available restoration functions is presented.

Riemer, T. E.↗
NASA NTRS1975

Ghost suppression in image restoration filtering

An optimum image restoration filter is described in which provision is made to constrain the spatial extent of the restoration function, the noise level of the filter output and the rate of falloff of the composite system point-spread away from the origin. Experimental results show that sidelobes on the composite system point-spread function produce ghosts in the restored image near discontinuities in intensity level. By redetermining the filter using a penalty function that is zero over the main lobe of the composite point-spread function of the optimum filter and nonzero where the point-spread function departs from a smoothly decaying function in the sidelobe region, a great reduction in sidelobe level is obtained. Almost no loss in resolving power of the composite system results from this procedure. By iteratively carrying out the same procedure even further reductions in sidelobe level are obtained. Examples of original and iterated restoration functions are shown along with their effects on a test image.

Riemer, T. E.↗
NASA NTRS1984

Image restoration of high resolution observations of the M87 jet

Image-restoration techniques are applied to high-resolution (FWHM 0.5-1.0 arcsec) plates of the M87 jet obtained with the CFH telescope by Nieto and Lelievre (1982), and their description of the optical jet is confirmed. Most of the features detected are similar to those shown by the VLA map of Biretta et al. (1982), having a resolution of 0.12 arcsec. In particular, the restored images show evidence for an elongated nucleus and for a very sharp discontinuity in knot A which is not perpendicular to the jet axis. It also seems that the start of the oscillations and this discontinuity are not related. This similarity at a 0.2-arcsec scale suggests no relativistic motion (v less than 25,000 km/sec) throughout the jet.

Lorre, J. J.↗
NASA NTRS1985

Constrained optimization for image restoration using nonlinear programming

The constrained optimization problem for image restoration, utilizing incomplete information and partial constraints, is formulated using nonlinear proramming techniques. This method restores a distorted image by optimizing a chosen object function subject to available constraints. The penalty function method of nonlinear programming is used. Both linear or nonlinear object function, and linear or nonlinear constraint functions can be incorporated in the formulation. This formulation provides a generalized approach to solve constrained optimization problems for image restoration. Experiments using this scheme have been performed. The results are compared with those obtained from other restoration methods and the comparative study is presented.

Yeh, C.-L.↗
DOE OSTI2015

TU-CD-BRA-12: Coupling PET Image Restoration and Segmentation Using Variational Method with Multiple Regularizations

Purpose: To propose a new variational method which couples image restoration with tumor segmentation for PET images using multiple regularizations. Methods: Partial volume effect (PVE) is a major degrading factor impacting tumor segmentation accuracy in PET imaging. The existing segmentation methods usually need to take prior calibrations to compensate PVE and they are highly system-dependent. Taking into account that image restoration and segmentation can promote each other and they are tightly coupled, we proposed a variational method to solve the two problems together. Our method integrated total variation (TV) semi-blind deconvolution and Mumford-Shah (MS) segmentation. The TV norm was used on edges to protect the edge information, and the L{sub 2} norm was used to avoid staircase effect in the no-edge area. The blur kernel was constrained to the Gaussian model parameterized by its variance and we assumed that the variances in the X-Y and Z directions are different. The energy functional was iteratively optimized by an alternate minimization algorithm. Segmentation performance was tested on eleven patients with non-Hodgkin’s lymphoma, and evaluated by Dice similarity index (DSI) and classification error (CE). For comparison, seven other widely used methods were also tested and evaluated. Results: The combination of TV and L{sub 2} regularizations effectively improved the segmentation accuracy. The average DSI increased by around 0.1 than using either the TV or the L{sub 2} norm. The proposed method was obviously superior to other tested methods. It has an average DSI and CE of 0.80 and 0.41, while the FCM method — the second best one — has only an average DSI and CE of 0.66 and 0.64. Conclusion: Coupling image restoration and segmentation can handle PVE and thus improves tumor segmentation accuracy in PET. Alternate use of TV and L2 regularizations can further improve the performance of the algorithm. This work was supported in part by National Natural Science Foundation of China (NNSFC), under Grant No.61375018, and Fundamental Research Funds for the Central Universities, under Grant No. 2012QN086. Wei Lu was supported in part by the National Institutes of Health (NIH) Grant No. R01 CA172638.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1977

Optimum constrained image restoration filters

The research described centered on development of an optimum image restoration filter (IRF) minimizing the radius of gyration of the corrected or composite system point-spread function (P-SF) subject to contraints, and reducing 2-dimensional spatial smearing or blurring of an image. The constraints are imposed on the radius of gyration of the IRF P-SF, the total restored image noise power, and the shape of the composite system frequency spectrum. The image degradation corresponds to mapping many points from the original image into a single resolution element. The P-SF is obtained as solution to a set of simultaneous differential equations obeying nonlinear integral constraints. Truncation errors due to edge effects are controlled by constraining the radius of gyration of the IRF P-SF. An iterative technique suppresses sidelobes of the composite system P-SF.

Riemer, T. E.↗
NASA NTRS1991

Small convolution kernels for high-fidelity image restoration

An algorithm is developed for computing the mean-square-optimal values for small, image-restoration kernels. The algorithm is based on a comprehensive, end-to-end imaging system model that accounts for the important components of the imaging process: the statistics of the scene, the point-spread function of the image-gathering device, sampling effects, noise, and display reconstruction. Subject to constraints on the spatial support of the kernel, the algorithm generates the kernel values that restore the image with maximum fidelity, that is, the kernel minimizes the expected mean-square restoration error. The algorithm is consistent with the derivation of the spatially unconstrained Wiener filter, but leads to a small, spatially constrained kernel that, unlike the unconstrained filter, can be efficiently implemented by convolution. Simulation experiments demonstrate that for a wide range of imaging systems these small kernels can restore images with fidelity comparable to images restored with the unconstrained Wiener filter.

Reichenbach, Stephen E.↗
NASA NTRS1992

HST image restoration: A comparison of pre- and post-servicing mission results

A variety of image restoration techniques (e.g., Wiener filter, Lucy-Richardson, MEM) have been applied quite successfully to the aberrated HST images. The HST servicing mission (scheduled for late 1993 or early 1994) will install a corrective optics system (COSTAR) for the Faint Object Camera and spectrographs and replace the Wide Field/Planetary Camera with a second generation instrument (WF/PC-II) having its own corrective elements. The image quality is expected to be improved substantially with these new instruments. What then is the role of image restoration for the HST in the long term? Through a series of numerical experiments using model point-spread functions for both aberrated and unaberrated optics, we find that substantial improvements in image resolution can be obtained for post-servicing mission data using the same or similar algorithms as being employed now to correct aberrated images. Included in our investigations are studies of the photometric integrity of the restoration algorithms and explicit models for HST pointing errors (spacecraft jitter).

Hanisch, R. J.↗
NASA NTRS1973

Optical Signal Processing: Poisson Image Restoration and Shearing Interferometry

Optical signal processing can be performed in either digital or analog systems. Digital computers and coherent optical systems are discussed as they are used in optical signal processing. Topics include: image restoration; phase-object visualization; image contrast reversal; optical computation; image multiplexing; and fabrication of spatial filters. Digital optical data processing deals with restoration of images degraded by signal-dependent noise. When the input data of an image restoration system are the numbers of photoelectrons received from various areas of a photosensitive surface, the data are Poisson distributed with mean values proportional to the illuminance of the incoherently radiating object and background light. Optical signal processing using coherent optical systems is also discussed. Following a brief review of the pertinent details of Ronchi's diffraction grating interferometer, moire effect, carrier-frequency photography, and achromatic holography, two new shearing interferometers based on them are presented. Both interferometers can produce variable shear.

Hong, Yie-Ming↗
NASA NTRS1986

Far-infrared image restoration analysis of the protostellar cluster in S140

Image restoration techniques are applied to one-dimensional scans at 50 and 100 microns of the protostellar cluster in S140. These measurements resolve the surrounding nebula clearly, and Fourier methods are used to match the effective beam profiles at these wavelengths. This allows the radial distribution of temperature and dust column density to be derived at a diffraction limited spatial resolution of 23 arcsec (0.1 pc). Evidence for heating of the S140 molecular cloud by a nearby ionization front is established, and the dissociation of molecules inside the ionization front is spatially well correlated with the heating of the dust. The far-infrared spectral distribution of the three near-infrared sources within 10 arcsesc of the cluster center is presented.

Lester, D. F.↗
NASA NTRS2009

Comparison of Image Restoration Methods for Lunar Epithermal Neutron Emission Mapping

Orbital measurements of neutrons by the Lunar Exploring Neutron Detector (LEND) onboard the Lunar Reconnaissance Orbiter are being used to quantify the spatial distribution of near surface hydrogen (H). Inferred H concentration maps have low signal-to-noise (SN) and image restoration (IR) techniques are being studied to enhance results. A single-blind. two-phase study is described in which four teams of researchers independently developed image restoration techniques optimized for LEND data. Synthetic lunar epithermal neutron emission maps were derived from LEND simulations. These data were used as ground truth to determine the relative quantitative performance of the IR methods vs. a default denoising (smoothing) technique. We review and used factors influencing orbital remote sensing of neutrons emitted from the lunar surface to develop a database of synthetic "true" maps for performance evaluation. A prior independent training phase was implemented for each technique to assure methods were optimized before the blind trial. Method performance was determined using several regional root-mean-square error metrics specific to epithermal signals of interest. Results indicate unbiased IR methods realize only small signal gains in most of the tested metrics. This suggests other physically based modeling assumptions are required to produce appreciable signal gains in similar low SN IR applications.

McClanahan, T. P.↗
NASA NTRS1991

Image restoration of R136 - The dense core of NGC 2070

We present results from the application of a new seeing deconvolution technique to images of the dense core of NGC 2070 = 30 Doradus (the controversial object R136a). We utilize a new maximum entropy algorithm capable of restoring images to very high resolution, even to subpixel accuracy. Images of the object in different colors, as well as comparisons with previous speckle results, have been used to check the validity of the results. Our images of R136 have an angular resolution approaching 0.2 arcsec, better than any direct images of this object published to date, and corroborate evidence that R136a is a dense star cluster core, rather than a single ultraluminous object.

Weir, N.↗
NASA NTRS1977

Image restoration consequences of the lack of a two variable fundamental theorem of algebra

It has been shown that, at least for one pair of otherwise attractive spaces of images and operators, singular convolution operators do not necessarily have nonsingular neighbors. This result is a nuisance in image restoration. It is suggested that this difficulty might be overcome if the following three conditions are satisfied: (1) a weaker constraint than absolute summability can be identified for useful operators: (2) if the z-transform of an operator has at most a finite number of zeros on the unit torus, then the inverse z-transform formula yields an inverse operator meeting the weaker constraint: and (3) operators whose z-transforms are zero in a set of real, closed curves on the unit torus have neighbors which are zero in only a finite set of points on the unit torus.

Kreznar, J. E.↗
NASA NTRS1986

Image restoration and superresolution as probes of small scale far-IR structure in star forming regions

Far-infrared continuum studies from the Kuiper Airborne Observatory are described that are designed to fully exploit the small-scale spatial information that this facility can provide. This work gives the clearest picture to data on the structure of galactic and extragalactic star forming regions in the far infrared. Work is presently being done with slit scans taken simultaneously at 50 and 100 microns, yielding one-dimensional data. Scans of sources in different directions have been used to get certain information on two dimensional structure. Planned work with linear arrays will allow us to generalize our techniques to two dimensional image restoration. For faint sources, spatial information at the diffraction limit of the telescope is obtained, while for brighter sources, nonlinear deconvolution techniques have allowed us to improve over the diffraction limit by as much as a factor of four. Information on the details of the color temperature distribution is derived as well. This is made possible by the accuracy with which the instrumental point-source profile (PSP) is determined at both wavelengths. While these two PSPs are different, data at different wavelengths can be compared by proper spatial filtering. Considerable effort has been devoted to implementing deconvolution algorithms. Nonlinear deconvolution methods offer the potential of superresolution -- that is, inference of power at spatial frequencies that exceed D lambda. This potential is made possible by the implicit assumption by the algorithm of positivity of the deconvolved data, a universally justifiable constraint for photon processes. We have tested two nonlinear deconvolution algorithms on our data; the Richardson-Lucy (R-L) method and the Maximum Entropy Method (MEM). The limits of image deconvolution techniques for achieving spatial resolution are addressed.

Lester, D. F.↗
NASA NTRS1991

Wiener-matrix image restoration beyond the sampling passband

A finer-than-sampling-lattice resolution image can be obtained using multiresponse image gathering and Wiener-matrix restoration. The multiresponse image gathering weighs the within-passband and aliased signal components differently, allowing the Wiener-matrix restoration filter to unscramble these signal components and restore spatial frequencies beyond the sampling passband of the photodetector array. A multiresponse images can be reassembled into a single minimum mean square error image with a resolution that is sq rt A times finer than the photodetector-array sampling lattice.

Rahman, Zia-Ur↗