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At least 415 records · Page 23

Investigation of spatial misregistration effects in multispectral scanner data

The author has identified the following significant results. A model for estimating the expected proportion of multiclass pixels in a scene was generalized and extended to include misregistration effects. Another substantial effort was the development of a simulation model to generate signatures to represent the distributions of signals from misregistered multiclass pixels, based on single class signatures. Spatial misregistration causes an increase in the proportion of multiclass pixels in a scene and a decorrelation between signals in misregistered data channels. The multiclass pixel proportion estimation model indicated that this proportion is strongly dependent on the pixel perimeter and on the ratio of the total perimeter of the fields in the scene to the area of the scene. Test results indicated that expected values computed with this model were similar to empirical measurements made of this proportion in four LACIE data segments.

Nalepka, R. F.↗

Development of a universal water signature for the LANDSAT-3 Multispectral Scanner, part 1

A generalized four channel hyperplane to discriminate water from nonwater was developed using LANDSAT-3 multispectral scaner (MSS) scenes and matching same/next day color infrared aerial photography. The MSS scenes varied in sun elevation angle from 40 to 58 deg. The 28 matching air photo frames contained over 1400 water bodies larger than one surface acre. A preliminary water discriminant, was used to screen the data and eliminate from further consideration all pixels distant from water in MSS spectral space. A linear discriminant was iteratively fitted to the labelled pixels. This discriminant correctly classified 98.7% of the water pixels and 98.6% of the nonwater pixels. The discriminant detected 91.3% of the 414 water bodies over 10 acres in surface area, and misclassified as water 36 groups of contiguous nonwater pixels.

Schlosser, E. H.↗

Area estimation of environmental phenomena from NOAA-n satellite data

A technique for documenting changes in size of NOAA-n pixels in order to calibrate the data for use in performing area calculations is described. Based on Earth-satellite geometry, a function for calculating the effective pixel size, measured in terms of ground area, on any given pixel was derived. The equation is an application of the law of sines plus an arclength formula. Effective pixel dimensions for NOAA 6 and 7 satellites for all pixels between nadir and the extreme view angles are presented. The NOAA 6 data were used to estimate the areas of several lakes, with an accuracy within 5%. Sources of error are discussed.

Tappan, G.↗

Thematic Mapper image quality: Preliminary results

Based on images analyzed so far, the band to band registration accuracy of the thematic mapper is very good. For bands within the same focal plane, the mean misregistrations are well within the specification, 0.2 pixels. For bands between the cooled and uncooled focal planes, there is a consistent mean misregistration of 0.5 pixels along-scan and 0.2-0.3 pixels across-scan. It exceeds the permitted 0.3 pixels for registration of bands between focal planes. If the mean misregistrations were removed by the data processing software, an analysis of the standard deviation of the misregistration indicates all band combinations would meet the registration specifications except for those including the thermal band. Analysis of the periodic noise in one image indicates a noise component in band 1 with a spatial frequency equivalent to 3.2 pixels in the along-scan direction.

Wrigley, R. C.↗

Investigation of several aspects of LANDSAT 4/5 data quality

A second quadrant from the Sacramento, CA scene 44/33 acquired by LANDSAT-4 was tested for band to band resolution. Results show that all measured misregistrations are within 0.03 pixels for similar band pairs. Two LANDSAT-5 scenes (one from Corpus Christi, TX and the other from Huntsville, AL) were also tested for band to band resolution. All measured misregistrations in the Texas scene are less than 0.03 pixels. The across scan misregistration Alabama scene is -0.66 pixels and thus needs correction. A 512 x 512 pixel area of the Pacific Ocean was corrected for the pixel offsets. Modulation transfer function analysis of the San Mateo Bridge using data from the San Francisco scene was accomplished.

Wrigley, R. C.↗

Visible charge-coupled device (CCD) focal plane design considerations for multispectral applications

The typical Multispectral Linear Array (MLA) Instrument mission would be to gather high-resolution, radiometrically accurate earth resources data in several spectral bands over a prolonged period of time. These bands would include the visible (VIS), near infrared (NIR) and short wavelength infrared. Silicon charge-coupled imaging devices (CCDs) can be assembled into contiguous pixel focal planes which will cover the VIS/NIR region and operate reliably for several years in a space environment. A typical MLA focal plane would have approximately 12,000 pixels, with a pixel-to-pixel registration requirement on the order of + or - 0.1 pixel. The technology to assemble such focal planes has been developed and is described. The problem of polarization sensitivity associated with certain types of focal plane assemblies is addressed. Radiation effects on CCDs are also discussed, and a practical solution to the problem through the use of shielding is described.

Sadowski, H.↗

An analysis of Landsat-4 Thematic Mapper geometric properties

Landsat-4 Thematic Mapper data of Washington, DC, Harrisburg, PA, and Salton Sea, CA were analyzed to determine geometric integrity and conformity of the data to known earth surface geometry. Several tests were performed. Intraband correlation and interband registration were investigated. No problems were observed in the intraband analysis, and aside from indications of slight misregistration between bands of the primary versus bands of the secondary focal planes, interband registration was well within the specified tolerances. A substantial number of ground control points were found and used to check the images' conformity to the Space Oblique Mercator (SOM) projection of their respective areas. The means of the residual offsets, which included nonprocessing related measurement errors, were close to the one pixel level in the two scenes examined. The Harrisburg scene residual mean was 28.38 m (0.95 pixels) with a standard deviation of 19.82 m (0.66 pixels), while the mean and standard deviation for the Salton Sea scene were 40.46 (1.35 pixels) and 30.57 m (1.02 pixels), respectively. Overall, the data were judged to be a high geometric quality with errors close to those targeted by the TM sensor design specifications.

Walker, R. E.↗

Spectroradiometric calibration of the Thematic Mapper and Multispectral Scanner system

Radiometric measurements were taken on the morning of the LANDSAT 5 Thematic Mapper overpass. The sky was cloud free and the sites were dry. Barnes multiband radiometer data were collected for a 4 x 4 pixel area and two fractional pixel areas of slightly higher and lower reflectances than the larger area. Helicopter color photography was obtained of all the ground areas. This photography will allow a detailed reflectance map of the 4 x 4 pixel are to be made and registered to the TM imagery to an accuracy of better than half a pixel. Spectropolarimeter data were also collected of the 4 x 4 pixel area from the helicopter. In addition, ground based solar radiometer data were collected to provide spectral extinction optical thickness valves. The radiative transfer theory used in the development of the Herman code which was used in predicting the TM entrance pupil spectral radiances from the ground based measurements is described.

Slater, P. N.↗

Method of measuring sea surface water temperature with a satellite including wideband passive synthetic-aperture multichannel receiver

A wideband passive synthetic-aperture multichannel receiver with an antenna is mounted on a satellite which travels in an orbit above the Earth passing over large bodies of water, e.g., the Atlantic Ocean. The antenna is scanned to receive signals over a wide frequency band from each incremental surface area (pixel) of the water which are related to the pixel's sea temperature. The received signals are fed to several channels which are tuned to separate selected frequencies. Their outputs are fed to a processor with a memory for storage. As the antenna points to pixels within a calibration area around a buoy of known coordinates, signals are likewise received and stored. Exactly measured sea temperature is received from the buoy. After passing over several calibration areas, a forward stepwise regression analysis is performed to produce an expression which selects the significant from the insignificant channels and assigns weights (coefficients) to them. The expression is used to determine the sea temperature at each pixel based on the signals received therefrom. Wind temperature, pressure, and wind speed at each pixel can also be calculated.

Stacey, J. M.↗

Surface vegetative biomass modelling from combined AVHRR and Landsat satellite data

A methodology for the estimation of regional biomass on the basis of Landsat and Polar Orbiter Satellite Advanced Very High Resolution Radiometer (AVHRR) imagery has been developed by the present study, which concentrated on the Sierra Nevada-Cascade Mountains ecological province of California. The Landsat data are only used initially, to calibrate the AVHRR-based biomass data. The essential element of the present approach is a 'pixel proportions' model. An integer block of Landsat pixels corresponds to each AVHRR pixel. The Landsat pixels are converted into biomass pixels using species biomass expression equations available in the literature.

Logan, T. L.↗

Thematic mapper image quality - Preliminary results

Based on images analyzed so far, the band to band registration accuracy of the thematic mapper is very good. For bands within the same focal plane, the mean misregistrations are well within the specification, 0.2 pixels. For bands between the cooled and uncooled focal planes, there is a consistent mean misregistration of 0.5 pixels along-scan and 0.2-0.3 pixels across-scan. It exceeds the permitted 0.3 pixels for registration of bands between focal planes. If the mean misregistrations were removed by the data processing software, an analysis of the standard deviation of the misregistration indicates all band combinations would meet the registration specifications except for those including the thermal band. Analysis of the periodic noise in one image indicates a noise component in band 1 with a spatial frequency equivalent to 3.2 pixels in the along-scan direction.

Wrigley, R. C.↗

Method and apparatus for contour mapping using synthetic aperture radar

By using two SAR antennas spaced a known distance, B, and oriented at substantially the same look angle to illuminate the same target area, pixel data from the two antennas may be compared in phase to determine a difference delta phi from which a slant angle theta is determined for each pixel point from an equation Delta phi = (2 pi B/lambda)sin(theta - alpha), where lambda is the radar wavelength and alpha is the roll angle of the aircraft. The height, h, of each pixel point from the aircraft is determined from the equation h = R cos theta, and from the known altitude, a, of the aircraft above sea level, the altitude (elevation), a', of each point is determined from the difference a - h. This elevation data may be displayed with the SAR image by, for example, quantizing the elevation at increments of 100 feet starting at sea level, and color coding pixels of the same quantized elevation. The distance, d, of each pixel from the ground track of the aircraft used for the display may be determined more accurately from the equation d = R sin theta.

Goldstein, R. M.↗

Causes of spurious features in spectral reflectance data

Several techniques are becoming common in the analysis of imaging spectrometer data that can lead to spurious absorption features or to changes in the position, width, and shape of actual absorption features. It is a common practice to calibrate AIS or other imaging spectrometer data by averaging each pixel along the flight line. The average is used to calibrate the spectral data by dividing the spectrum at each pixel by the average. If some pixels in the data set contain an absorption, then the average will also show an absorption. Some AIS data has had problems with wavelength stability from one scan line to the next which can produce spurious features with some analysis methods. If a pixel has a spectrum with an absorption having a different position or width than the spectrum used in a ratio, then the ratio can produce a spurious absorption at a different position and width than the true absorption feature. An average spectrum ratioed to each pixel will produce band shifts, and changes in width or shape. If continuum removal is performed by substraction rather than division, band positions can also be shifted.

Clark, Roger N.↗

A gridding approach to detect patterns of change in coastal wetlands from digital data

The conversion of land to water or water to land in the Grand Bayou wetlands area from 1972 to 1981 is evaluated on the basis of Landsat MSS band 2 and 4 images. A postclassification (land vs water) procedure is employed, and grids 1, 5, 10, 25, and 50 pixels square are superimposed on the classified data in an effort to reduce the effects of poor georegistration of the images (simulated by shifting one set of grids two pixels vertically and horizontally). The results are presented in tables, maps, and sample images and characterized in detail. Grids 5 or 10 pixels square are found to give percentage land/water change values and locations similar to those obtained in pixel-by-pixel analysis of nearly perfectly matched images.

Pelletier, R. E.↗

Real-time processor for staring receivers

The design, fabrication, and testing of a state-of-the-art, high-throughput on-focal plane IR-image signal processor is described. The processing functions performed are frame differencing and thresholding. The final focal plane array will consist of a 128 x 128-pixel platinum-silicide detector bump-mounted to an on-chip CCD multiplexer. The processor is in a 128-channel parallel-pipeline format. Each channel consists of a pixel regenerator (charge differencer), 128-pixel frame store CCD memory, pixel differencer, second pixel regenerator, thresholder (analog comparator), and digital latch. Four parallel analog outputs and four parallel digital outputs are included. The digital outputs provide a bit map of the image. All analog clock signals (128 KHz, 256 KHz, and 5 MHz) are generated by on-chip TTL-input clock drivers. TTL clock driver inputs are generated off-chip. The technology is low-temperature surface and buried channel CCD/CMOS/indium bump. The design goal was 8-bit resolution at 77 K and 1000 frames/s. Applications include point- or extended-target motion detection with thresholding. Design trade-offs and enhancements (such as on-chip detector gain compensation and a simple window processor) are discussed.

Hanzal, Brian↗

ACE: Automatic Centroid Extractor for real time target tracking

A high performance video image processor has been implemented which is capable of grouping contiguous pixels from a raster scan image into groups and then calculating centroid information for each object in a frame. The algorithm employed to group pixels is very efficient and is guaranteed to work properly for all convex shapes as well as most concave shapes. Processing speeds are adequate for real time processing of video images having a pixel rate of up to 20 million pixels per second. Pixels may be up to 8 bits wide. The processor is designed to interface directly to a transputer serial link communications channel with no additional hardware. The full custom VLSI processor was implemented in a 1.6 mu m CMOS process and measures 7200 mu m on a side.

Cameron, K.↗

A summary of image segmentation techniques

Machine vision systems are often considered to be composed of two subsystems: low-level vision and high-level vision. Low level vision consists primarily of image processing operations performed on the input image to produce another image with more favorable characteristics. These operations may yield images with reduced noise or cause certain features of the image to be emphasized (such as edges). High-level vision includes object recognition and, at the highest level, scene interpretation. The bridge between these two subsystems is the segmentation system. Through segmentation, the enhanced input image is mapped into a description involving regions with common features which can be used by the higher level vision tasks. There is no theory on image segmentation. Instead, image segmentation techniques are basically ad hoc and differ mostly in the way they emphasize one or more of the desired properties of an ideal segmenter and in the way they balance and compromise one desired property against another. These techniques can be categorized in a number of different groups including local vs. global, parallel vs. sequential, contextual vs. noncontextual, interactive vs. automatic. In this paper, we categorize the schemes into three main groups: pixel-based, edge-based, and region-based. Pixel-based segmentation schemes classify pixels based solely on their gray levels. Edge-based schemes first detect local discontinuities (edges) and then use that information to separate the image into regions. Finally, region-based schemes start with a seed pixel (or group of pixels) and then grow or split the seed until the original image is composed of only homogeneous regions. Because there are a number of survey papers available, we will not discuss all segmentation schemes. Rather than a survey, we take the approach of a detailed overview. We focus only on the more common approaches in order to give the reader a flavor for the variety of techniques available yet present enough details to facilitate implementation and experimentation.

Spirkovska, Lilly↗

A monolithic Si bolometer array for the Caltech Submillimeter Observatory

We are developing a submillimeter continuum camera for the Caltech Submillimeter Observatory (CSO) located on Mauna Kea. The camera will employ a monolithic Si bolometer array which was developed by Moseley et al. at the NASA Goddard Space Flight Center (GSFC). The camera will be cooled to a temperature of about 300 mK in a He-3 cryostat, and will operate primarily at wavelengths of 350 and 450 micrometers. We plan to use a bolometer array with 1x24 directly illuminated pixels, each pixel of dimension 1x2 sq mm, which is about half of the F/4 beam size at these wavelengths. Each pixel is 10 to 12 micrometers thick and is supported only by four thin Si legs formed by wet chemical etch. The pixels are doped n-type by phosphorus implantation, compensated by boron implantation. Signals from the bolometer pixels are first amplified by cryogenically cooled FET's. The signals are further amplified by room-temperature amplifiers and then separately digitized by 16 bit A/D converters with differential inputs. The outputs of the A/D converters are fed into a digital signal processing board via fiber-optic cables. The electronics and data acquisition system were designed by the Goddard group. We will report the status of this effort.

Wang, Ning↗