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The image dissector sensor for the Earth Resources Program is evaluated using contrast and reflectance data. The ground resolution obtainable for low contrast at the targeted signal to noise ratio of 1.8 was defined. It is concluded that the system is capable of achieving the detection of small, low contrast ground targets from satellites.
Orbital imagery for planetary exploration - imaging sensor system scaling laws
The Harwell Image Processing System (HIPS) has been adapted for processing earth-resource imagery in either film or tape format. Data from film are obtained using a computer-controlled flying-spot scanner. Local rapid interactive processing is based on a PDP 11/20 minicomputer which has suitable display facilities for immediate visual appraisal of results and also a fast data link to an IBM 370/168 computer complex. An extensive subroutine library is being assembled for data preprocessing and feature extraction. This chapter includes a discussion of the basic principles of image analysis, a description of the HIPS system, and finally, for illustrative purposes, a description of several simple software routines.
The effects of different types of imaging data compression on the elements of the Pioneer end-to-end data system were studied for three imaging transmission methods. These were: no data compression, moderate data compression, and the advanced imaging communications system. It is concluded that: (1) the value of data compression is inversely related to the downlink telemetry bit rate; (2) the rolling characteristics of the spacecraft limit the selection of data compression ratios; and (3) data compression might be used to perform acceptable outer planet mission at reduced downlink telemetry bit rates.
The imaging photopolarimeter aboard the Pioneer 10 spacecraft en route to the vicinity of Jupiter is described. This instrument is capable of moderate resolution spin-scan imaging and high precision polarimetric and photometric mapping of Jupiter in red and blue light. The field of view can be selectively changed from 0.50 mrad square to 40 mrad square to accommodate resolution and radiance combinations ranging from the zodiacal background to that of Jupiter. Optical materials were chosen to survive, with minimum degradation, the rigors of a nearly 2-year journey to Jupiter including transit through the Jovian trapped radiation belts. The optics are described in detail, and the operational system is outlined. The procedures for preflight and in-flight calibration are described, and some performance characteristics and preliminary flight results are presented.
A high speed, high-resolution flow imaging system is modified to achieve extended depth of field imaging. An optical distortion element is introduced into the flow imaging system. Light from an object, such as a cell, is distorted by the distortion element, such that a point spread function (PSF) of the imaging system is invariant across an extended depth of field. The distorted light is spectrally dispersed, and the dispersed light is used to simultaneously generate a plurality of images. The images are detected, and image processing is used to enhance the detected images by compensating for the distortion, to achieve extended depth of field images of the object. The post image processing preferably involves de-convolution, and requires knowledge of the PSF of the imaging system, as modified by the optical distortion element.
A high speed, high-resolution flow imaging system is modified to achieve extended depth of field imaging. An optical distortion element is introduced into the flow imaging system. Light from an object, such as a cell, is distorted by the distortion element, such that a point spread function (PSF) of the imaging system is invariant across an extended depth of field. The distorted light is spectrally dispersed, and the dispersed light is used to simultaneously generate a plurality of images. The images are detected, and image processing is used to enhance the detected images by compensating for the distortion, to achieve extended depth of field images of the object. The post image processing preferably involves de-convolution, and requires knowledge of the PSF of the imaging system, as modified by the optical distortion element.
Image spatial resolution characteristics can vary widely among sources. In the case of aerial-based imaging systems, the image spatial resolution characteristics can even vary between acquisitions. In these systems, aircraft altitude, speed, and sensor look angle all affect image spatial resolution. Image spatial resolution needs to be verified with estimators that include the ground sample distance (GSD), the modulation transfer function (MTF), and the relative edge response (RER), all of which are key components of image quality, along with signal-to-noise ratio (SNR) and dynamic range. Knowledge of spatial resolution parameters is important to determine if features of interest are distinguishable in imagery or associated products, and to develop image restoration algorithms. An automated Spatial Resolution Verification Tool (SRVT) was developed to rapidly determine the spatial resolution characteristics of remotely sensed aerial and satellite imagery. Most current methods for assessing spatial resolution characteristics of imagery rely on pre-deployed engineered targets and are performed only at selected times within preselected scenes. The SRVT addresses these insufficiencies by finding uniform, high-contrast edges from urban scenes and then using these edges to determine standard estimators of spatial resolution, such as the MTF and the RER. The SRVT was developed using the MATLAB programming language and environment. This automated software algorithm assesses every image in an acquired data set, using edges found within each image, and in many cases eliminating the need for dedicated edge targets. The SRVT automatically identifies high-contrast, uniform edges and calculates the MTF and RER of each image, and when possible, within sections of an image, so that the variation of spatial resolution characteristics across the image can be analyzed. The automated algorithm is capable of quickly verifying the spatial resolution quality of all images within a data set, enabling the appropriate use of those images in a number of applications.
Mallinckrodt Institute of Radiology (MIR) is using a digital image processing system which employs NASA-developed technology. MIR's computer system is the largest radiology system in the world. It is used in diagnostic imaging. Blood vessels are injected with x-ray dye, and the images which are produced indicate whether arteries are hardened or blocked. A computer program developed by Jet Propulsion Laboratory known as Mini-VICAR/IBIS was supplied to MIR by COSMIC. The program provides the basis for developing the computer imaging routines for data processing, contrast enhancement and picture display.
The goal of this research is to develop a robust control strategy for constructing image understanding systems (IUS). This paper proposes a general framework based on the integration of related hypotheses. Hypotheses are regarded as predictions of the occurrences of objects in the image. Related hypotheses are clustered together. A composite hypothesis is computed for each cluster. The goal of the IUS is to verify the hypotheses. We constructed an image understanding system, SIGMA, based on this framework and demonstrated its performance on an aerial image of a suburban housing development.
The relationship between the image gathering and image processing systems for minimum mean squared error estimation of scene characteristics is investigated. A stochastic optimization problem is formulated where the objective is to determine a spatial characteristic of the scene rather than a feature of the already blurred, sampled and noisy image data. An analytical solution for the optimal characteristic image processor is developed. The Wiener filter for the sampled image case is obtained as a special case, where the desired characteristic is scene restoration. Optimal edge detection is investigated using the Laplacian operator x G as the desired characteristic, where G is a two dimensional Gaussian distribution function. It is shown that the optimal edge detector compensates for the blurring introduced by the image gathering optics, and notably, that it is not circularly symmetric. The lack of circular symmetry is largely due to the geometric effects of the sampling lattice used in image acquisition. The optimal image gathering optical transfer function is also investigated and the results of a sensitivity analysis are shown.
Quantitative optical gas imaging (QOGI) system can rapidly quantify leaks detected by optical gas imaging (OGI) cameras across the oil and gas supply chain. A comprehensive evaluation of the QOGI system’s quantification capability is needed for the successful adoption of the technology. This study conducted single-blind experiments to examine the quantification performance of the FLIR QL320 QOGI system under near-field conditions at a pseudo-realistic, outdoor, controlled testing facility that mimics upstream and midstream natural gas operations. The study completed 357 individual measurements across 26 controlled releases and 71 camera positions for release rates between 0.1 kg Ch 4 /h and 2.9 kg Ch 4 /h of compressed natural gas (which accounts for more than 90% of typical component-level leaks in several production facilities). The majority (75%) of measurements were within a quantification factor of 3 (quantification error of –67% to 200%) with individual errors between –90% and 831%, which reduced to –79% to +297% when the mean of estimates of the same controlled release from multiple camera positions was considered. Performance improved with increasing release rate, using clear sky as plume background, and at wind speeds ≤1 mph relative to other measurement conditions.
Meteor photographic recording with image orthicon tube
The Spectral Image Processing System (SIPS) is a software package developed by the Center for the Study of Earth from Space (CSES) at the University of Colorado, Boulder, in response to a perceived need to provide integrated tools for analysis of imaging spectrometer data both spectrally and spatially. SIPS was specifically designed to deal with data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the High Resolution Imaging Spectrometer (HIRIS), but was tested with other datasets including the Geophysical and Environmental Research Imaging Spectrometer (GERIS), GEOSCAN images, and Landsat TM. SIPS was developed using the 'Interactive Data Language' (IDL). It takes advantage of high speed disk access and fast processors running under the UNIX operating system to provide rapid analysis of entire imaging spectrometer datasets. SIPS allows analysis of single or multiple imaging spectrometer data segments at full spatial and spectral resolution. It also allows visualization and interactive analysis of image cubes derived from quantitative analysis procedures such as absorption band characterization and spectral unmixing. SIPS consists of three modules: SIPS Utilities, SIPS_View, and SIPS Analysis. SIPS version 1.1 is described below.
Monograph presents comprehensive overview of science and technology of spaceborne microwave-imaging systems. Microwave images used as versatile orbiting, remote-sensing systems to investigate atmospheres and surfaces of planets. Detect surface objects through canopies of clouds, measure distributions of raindrops in clouds that their views penetrate, find meandering rivers in rain forests and underground water in arid regions, and provide information on ocean currents, wakes, ice/water boundaries, aircraft, ships, buoys, and bridges.
A study of boundary-layer flow regimes on a NACA 0012 airfoil from zero angle of attack up to separation is presented. The boundary-layer transition from the laminar to the turbulent regime and the onset of the separation were detected by surface thermography of the airfoil performed with an infrared imaging system. The findings were compared with observations of aluminum-foil tufts visible with the infrared imaging system. This arrangement allows the infrared imaging system to assume the dual role of flow regime detection through surface thermography and flow visualization through the observation of the aluminum-foil tufts. Ultimately the temperature history on an uncontaminated surface could provide an interpretation of the state of boundary-layer flow. Separation studies performed on the NACA 0012 airfoil showed that aluminum foil tufts can be observed with infrared imaging systems.
An optical image enhancement system provides improved image contrast in imaging of a target in high temperature surroundings such as a furnace. The optical system includes a source of vertically polarized light such as laser and a beam splitter for receiving the light and directing the light toward the target. A retardation plate is affixed to a target-facing surface of the beam splitter and a vertical polarizer is disposed along a common optical path with the beam splitter between the retardation plate and the target. A horizontal polarizer disposed in the common optical path, receives light passing through a surface of the beam splitter opposed to the target-facing surface. An image detector is disposed at one end of the optical path. A band pass filter having a band pass filter characteristic matching the frequency of the vertically polarized light source is disposed in the path between the horizontal polarizer and the image detector. The use of circular polarization, together with cross polarizers, enables the reflected light to be passed to the detector while blocking thermal radiation.
Description of the image-processing system for the Earth Resources Technology Satellite (ERTS), which will process video-tape recordings received from the satellite into imagery and digitized video data suitable for earth-resource study and analysis. The system is made up of three subsystems. The bulk processor produces 70-mm images and digitized records, corrected for systematic geometric and radiometric errors as well as for sensor-calibration and other errors. The precision processor modifies the bulk images to significantly increase geometric precision. The special processor transfers either bulk or precision data to computer-compatible tape.