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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

A quantitative assessment of resampling errors

Applications associated with digital geographic imagery are subject to great diversity in required cell size, cartographic projection, etc. The need for resampling remote sensing scaner data is evident in all but the most undemanding cases. It is shown that proper resampling of such data is dependent in important ways on the detailed knowledge of the original scanner's effective point-spread function and to the desired point-spread function of resampled data. When both of these are known, it is relatively straightforward to compute the resampling coefficients which do the best job of approximating the shape and position of the synthesized point-spread function. The resulting synthesized psf are compared with an ideal psf located at various interpixel positions and any differences observed as errors.

Dye, R. H.↗
DOE OSTI2016

WE-DE-207B-05: Measuring Spatial Resolution in Digital Breast Tomosynthesis: Update of AAPM Task Group 245

Purpose: Spatial resolution in digital breast tomosynthesis (DBT) is affected by inherent/binned detector resolution, oblique entry of x-rays, and focal spot size/motion; the limited angular range further limits spatial resolution in the depth-direction. While DBT is being widely adopted clinically, imaging performance metrics and quality control protocols have not been standardized. AAPM Task Group 245 on Tomosynthesis Quality Control has been formed to address this deficiency. Methods: Methods of measuring spatial resolution are evaluated using two prototype quality control phantoms for DBT. Spatial resolution in the detector plane is measured in projection and reconstruction domains using edge-spread function (ESF), point-spread function (PSF) and modulation transfer function (MTF). Spatial resolution in the depth-direction and effective slice thickness are measured in the reconstruction domain using slice sensitivity profile (SSP) and artifact spread function (ASF). An oversampled PSF in the depth-direction is measured using a 50 µm angulated tungsten wire, from which the MTF is computed. Object-dependent PSF is derived and compared with ASF. Sensitivity of these measurements to phantom positioning, imaging conditions and reconstruction algorithms is evaluated. Results are compared from systems of varying acquisition geometry (9–25 projections over 15–60°). Dependence of measurements on feature size is investigated. Results: Measurements of spatial resolution using PSF and LSF are shown to depend on feature size; depth-direction spatial resolution measurements are shown to similarly depend on feature size for ASF, though deconvolution with an object function removes feature size-dependence. A slanted wire may be used to measure oversampled PSFs, from which MTFs may be computed for both in-plane and depth-direction resolution. Conclusion: Spatial resolution measured using PSF is object-independent with sufficiently small object; MTF is object-independent. Depth-direction spatial resolution may be measured directly using MTF or indirectly using ASF or SSP as surrogate measurements. While MTF is object-independent, it is invalid for nonlinear reconstructions.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2007

On-orbit Modulation Transfer Function (MTF) Measurements for IKONOS and QuickBird

Point Spread Function is a method of evaluation the spatial resolution of an imaging system. It is also a measure of the spread of a single point of light. Modulation Transfer Function (MTF) is a measure of the spatial frequency response. It is often calculated from th point spread function (PSF). System response at the Nyquist frequency (or 0.5 cycle/pixel) is often used as a figure of merit

Helde, Dennis↗
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 NTRS1977

The effects of the atmospheric point-spread 'seeing' function on spatially resolved spectra of Jupiter

We present the results of an analysis of the effects of atmospheric seeing and of instrumental spectral and spatial resolution on the observed variation of absorption-line profiles across the disk of Jupiter. The technique described may be applied equally well to the analysis of observations of any extended astronomical source. These results show the necessity of obtaining accurate point-spread-function information during the course of observations of this nature. We also point out that in order to avoid the uncertainties and ambiguities inherent in attempts at deconvolution of observational data, one must properly convolve the appropriate spatial and spectral resolution functions with the models being tested and then compare the results with the observational data.

Gelfand, J.↗
DOE OSTI2020

Reduced Artifact Approach for Determining Diffusion Coefficients in Time-Resolved Microscopy

Ultrafast microscopy methods traditionally assume a Gaussian profile to extract excited state diffusivities from transport measurements. Although this fitting method recovers accurate diffusion coefficients when the point spread function is well-represented by a Gaussian, even minor spatial aberrations introduced by the imaging system cause significant errors in the determined value. To provide a more accurate measure of excited state transport in nano- and microscale materials systems, in this work an alternative analysis protocol is proposed that numerically convolves the Green’s function solution to the diffusion equation with the experimentally measured point spread function. In contrast to the Gaussian fitting approach, the numerical convolution is shown to be robust against artifacts caused by nonideal point spread functions. Furthermore, the numerical convolution approach is highly effective at resolving anisotropic diffusion in modeled data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Information-rich localization microscopy through machine learning

Recent years have witnessed the development of single-molecule localization microscopy as a generic tool for sampling diverse biologically relevant information at the super-resolution level. While current approaches often rely on the target-specific alteration of the point spread function to encode the multidimensional contents of single fluorophores, the details of the point spread function in an unmodified microscope already contain rich information. Here we introduce a data-driven approach in which artificial neural networks are trained to make a direct link between an experimental point spread function image and its underlying, multidimensional parameters, and compare results with alternative approaches based on maximum likelihood estimation. To demonstrate this concept in real systems, we decipher in fixed cells both the colors and the axial positions of single molecules in regular localization microscopy data.

42 ENGINEERING↗
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.↗
DOE OSTI2020

Scintillator detector characterization for laser-driven proton beam imaging

The spatial resolution and imaging characteristics of plastic scintillators are characterized using laser-driven proton beams. Laser-driven proton beams typically have broad energy spectra and are accompanied by relativistic electrons and high-energy photons, both potentially contributing to background noise. Different types and thicknesses of Eljen Technology scintillators are compared to determine their intrinsic point spread function. Point-projection imaging of a mesh is used to compare the imaging resolution of the scintillator to the usual imaging detector, radiochromic film, and is found to be reasonably comparable and sufficient for many experimental applications.

47 OTHER INSTRUMENTATION↗
NASA NTRS1982

Report of subpanel on image sharpness

Factors effecting the sharpness of images acquired by multispectral scanners, synthetic aperture radar, thermal infrared sensors, and multispectral linear arrays are defined. Factors associated with the sensor include the atmospheric blur/scatter function, the point spread function of the sensor, the sensor aperture, the filter characteristics, and the sampling rate and quatization effects. Several research tasks are proposed which include investigating the use of optical prefilters which include investigating the use of optical prefilters and the relationships of the instantaneous field of view (aperture width) on the performance of geocorrelation systems.

Source record↗
NASA NTRS2003

Parameters Describing Earth Observing Remote Sensing Systems

The Earth science community needs to generate consistent and standard definitions for spatial, spectral, radiometric, and geometric properties describing passive electro-optical Earth observing sensors and their products. The parameters used to describe sensors and to describe their products are often confused. In some cases, parameters for a sensor and for its products are identical; in other cases, these parameters vary widely. Sensor parameters are bound by the fundamental performance of a system, while product parameters describe what is available to the end user. Products are often resampled, edge sharpened, pan-sharpened, or compressed, and can differ drastically from the intrinsic data acquired by the sensor. Because detailed sensor performance information may not be readily available to an international science community, standardization of product parameters is of primary performance. Spatial product parameters described include Modulation Transfer Function (MTF), point spread function, line spread function, edge response, stray light, edge sharpening, aliasing, ringing, and compression effects. Spectral product parameters discussed include full width half maximum, ripple, slope edge, and out-of-band rejection. Radiometric product properties discussed include relative and absolute radiometry, noise equivalent spectral radiance, noise equivalent temperature diffenence, and signal-to-noise ratio. Geometric product properties discussed include geopositional accuracy expressed as CE90, LE90, and root mean square error. Correlated properties discussed include such parameters as band-to-band registration, which is both a spectral and a spatial property. In addition, the proliferation of staring and pushbroom sensor architectures requires new parameters to describe artifacts that are different from traditional cross-track system artifacts. A better understanding of how various system parameters affect product performance is also needed to better ascertain the utility of existing datasets and products as well as to specify the performance of new sensors and products. Examples of simulations performed for the Landsat Data Continuity Mission illustrate how various parameters affect system and product performance. Specific examples include the effects of ground sample distance, MTF, and band-to-band registration on various products.

Zanoni, Vicki↗
NASA NTRS2006

Estimating Temperature Retrieval Accuracy Associated With Thermal Band Spatial Resolution Requirements for Center Pivot Irrigation Monitoring and Management

This study explores the use of synthetic thermal center pivot irrigation scenes to estimate temperature retrieval accuracy for thermal remote sensed data, such as data acquired from current and proposed Landsat-like thermal systems. Center pivot irrigation is a common practice in the western United States and in other parts of the world where water resources are scarce. Wide-area ET (evapotranspiration) estimates and reliable water management decisions depend on accurate temperature information retrieval from remotely sensed data. Spatial resolution, sensor noise, and the temperature step between a field and its surrounding area impose limits on the ability to retrieve temperature information. Spatial resolution is an interrelationship between GSD (ground sample distance) and a measure of image sharpness, such as edge response or edge slope. Edge response and edge slope are intuitive, and direct measures of spatial resolution are easier to visualize and estimate than the more common Modulation Transfer Function or Point Spread Function. For these reasons, recent data specifications, such as those for the LDCM (Landsat Data Continuity Mission), have used GSD and edge response to specify spatial resolution. For this study, we have defined a 400-800 m diameter center pivot irrigation area with a large 25 K temperature step associated with a 300 K well-watered field surrounded by an infinite 325 K dry area. In this context, we defined the benchmark problem as an easily modeled, highly common stressing case. By parametrically varying GSD (30-240 m) and edge slope, we determined the number of pixels and field area fraction that meet a given temperature accuracy estimate for 400-m, 600-m, and 800-m diameter field sizes. Results of this project will help assess the utility of proposed specifications for the LDCM and other future thermal remote sensing missions and for water resource management.

Ryan, Robert E.↗
NASA NTRS1984

LANDSAT-4 image data quality analysis

Methods were developed for estimating point spread functions from image data. Roads and bridges in dark backgrounds are being examined as well as other smoothing methods for reducing noise in the estimated point spread function. Tomographic techniques were used to estimate two dimensional point spread functions. Reformatting software changes were implemented to handle formats for LANDSAT-5 data.

Anuta, P. E.↗
NASA NTRS1986

Centroid tracking with area array detectors

A computer program (ALGEVAL) has been developed to simulate the position estimating behavior of a centroid estimator algorithm using data typical of optical point spread function data recorded by an area array detector. Typical results are shown of varying detector properties and optical point spread function types. The detector parameters currently available for study include read noise mean value, dark current mean value and spatial variation, charge transfer efficiency and point spread function location, saturation level, signal level and pixel size. The program is capable of calculating any order centroid using an array size from 2 x 2 to 15 x 15 pixels. The output of the program is either a performance map, histogram data or tabluar data. A number of further developments are recommended.

Glavich, T. A.↗
DOE OSTI2026

Characterizing degraded visual environments with scanning lenses to improve contrast recovery

Atmospheric aerosols, such as fog and smoke, degrade optical signals via the scattering and absorption of light, making it difficult to recover information from the surrounding environment. Here, we present a technique that measures the angular distribution of light in scattering environments to help recover these degraded optical signals. This is done by passing a collimated beam through the aerosol environment and collecting the scattered and unscattered light with an f-theta scan lens. The lens transforms the angular distribution of the scattered light into the linear domain, mapping the collected light onto a detector. The measured angular scattering distribution is then used to estimate the point spread function of the environment at an arbitrary stand-off distance. This point spread function can be used to deconvolve images blurred by the aerosol environment in which the angular scattering distribution was initially measured. With this approach, we demonstrate improvements in the effective resolution of deblurred images up to 26% over a 120-cm stand-off distance. Experimentation was performed in the Sandia National Laboratories tabletop fog chamber, a platform that generates aerosol environments analogous to real-world fogs. We intend to leverage this technique in future work to develop a low-SWaP system for the in situ characterization of aerosol environments.

Aerosols↗
NASA NTRS1984

Image Quality on the KAO

Three flights of the Kuiper Airborne Observatory (KAO) were taken to study the cause of the point spread function (PSF) degradation. The preliminary conclusions are: (1) the KAO point spread function decreases in size with elapsed time at altitude; (2) image motion is occasionally comparable to the size of the image, but is usually a sub-arcsecond effect; and (3) star images show small scale internal structural changes on a 200 microsecond timescale.

Dunham, E. W.↗
NASA NTRS1993

Measurements of microlens performance

We present results of laboratory evaluations of several microlens types that have been designed and fabricated at the Lockheed Research and Development Division. The microlenses include wideband and dispersive types, in isolation and in arrays, and fabricated with binary or grayscale methods. Different lens pixel geometries are considered, including square, hexagonal, and skewed microlenses. We describe our micro-optics laboratory testbed which has been designed for the evaluation of individual lenslets or 2D arrays at selected spectral wavelengths. Measurement capabilities include focal length, point-spread functions, wavefront quality, and modulation transfer functions. Our present effort focuses on the results of point spread function measurements and their comparison with design predictions.

Shough, D.↗
DOE OSTI2018

Interparameter trade-off quantification and reduction in isotropic-elastic full-waveform inversion: synthetic experiments and Hussar land data set application

The problem of inverting for multiple physical parameters in the subsurface using seismic full-waveform inversion (FWI) is complicated by interparameter trade-off arising from inherent ambiguities between different physical parameters. Parameter resolution is often characterized using scattering radiation patterns, but these neglect some important aspects of interparameter trade-off. More general analysis and mitigation of interparameter trade-off in isotropic-elastic FWI is possible through judiciously chosen multiparameter Hessian matrix-vector products. We show that products of multiparameter Hessian off-diagonal blocks with model perturbation vectors, referred to as interparameter contamination kernels , are central to the approach. We then apply the multiparameter Hessian to various vectors designed to provide information regarding the strengths and characteristics of interparameter contamination, both locally and within the whole volume. With numerical experiments, we observe that S-wave velocity perturbations introduce strong contaminations into density and phase-reversed contaminations into P-wave velocity, but themselves experience only limited contaminations from other parameters. Based on these findings, we introduce a novel strategy to mitigate the influence of interparameter trade-off with approximate contamination kernels. Furthermore, we recommend that the local spatial and interparameter trade-off of the inverted models be quantified using extended multiparameter point spread functions (EMPSFs) obtained with pre-conditioned conjugate-gradient algorithm. Compared to traditional point spread functions, the EMPSFs appear to provide more accurate measurements for resolution analysis, by de-blurring the estimations, scaling magnitudes and mitigating interparameter contamination. Approximate eigenvalue volumes constructed with stochastic probing approach are proposed to evaluate the resolution of the inverted models within the whole model. With a synthetic Marmousi model example and a land seismic field data set from Hussar, Alberta, Canada, we confirm that the new inversion strategy suppresses the interparameter contamination effectively and provides more reliable density estimations in isotropic-elastic FWI as compared to standard simultaneous inversion approach.

58 GEOSCIENCES↗