Revised Point-spread Functions for the Atmospheric Imaging Assembly on board the Solar Dynamics Observatory
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Stefan J. Hofmeister↗
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Results for “point spread function”
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Coma Off It: Regularizing Variable Point-spread Functions
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J. Marcus Hughes↗
An on Orbit Determination of Point Spread Functions for the Interface Region Imaging Spectrograph
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Hans Courrier↗
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.↗
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↗
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.↗
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.↗
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.↗
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.
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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↗
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.↗
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.↗
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.↗
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↗
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.↗
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.↗
Spatial and spectral simulation of LANDSAT images of agricultural areas
A LANDSAT scene simulation capability was developed to study the effects of small fields and misregistration on LANDSAT-based crop proportion estimation procedures. The simulation employs a pattern of ground polygons each with a crop ID, planting date, and scale factor. Historical greenness/brightness crop development profiles generate the mean signal values for each polygon. Historical within-field covariances add texture to pixels in each polygon. The planting dates and scale factors create between-field/within-crop variation. Between field and crop variation is achieved by the above and crop profile differences. The LANDSAT point spread function is used to add correlation between nearby pixels. The next effect of the point spread function is to blur the image. Mixed pixels and misregistration are also simulated.
Pont, W. F., Jr.↗
Spatial and spectral simulation of Landsat images of agricultural areas
A Landsat scene simulation capability was developed to study the effects of small fields and misregistration on Landsat-based crop proportion estimation procedures. The simulation employs a pattern of ground polygons each with a crop ID, planting date, and scale factor. Historical greenness/brightness crop development profiles generate the mean signal values for each polygon. Historical within-field covariances add texture to pixels in each polygon. The planting dates and scale factors create between-field/within-crop variation. Between field and crop variation is achieved by the above and crop profile differences. The Landsat point spread function is used to add correlation between nearby pixels. The next effect of the point spread function is to blur the image. Mixed pixels and misregistration are also simulated. Previously announced in STAR as N82-32813
Pont, W. F., Jr.↗