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The TXI was flown successfully on 21 June 2001 (36.199 US). All systems functioned as planned and image data were acquired and sent to the ground. Unfortunately, due to a parachute failure the payload was destroyed. In this report we summarize results from the flight and provide detailed information on the high resolution X-ray imaging detector which was developed as part of the program.
Many imaging applications require quantitative determination of a scene's spectral radiance. This paper describes a new system capable of real-time spectroradiometric imagery. Operating at a full-spectrum update rate of 30Hz, this imager is capable of collecting a 30 point spectrum from each of three imaging heads: the first operates from 400 nm to 950 nm, with a 2% bandwidth; the second operates from 1.5 micro-m to 5.5 micro-m with a 1.5% bandwidth; the third operates from 5 micro-m to 12 micro-m, also at a 1.5% bandwidth. Standard image format is 256 x 256, with 512 x 512 possible in the VIS/NIR head. Spectra of up to 256 points are available at proportionately lower frame rates. In order to make such a tremendous amount of data more manageable, internal processing electronics perform four important operations on the spectral imagery data in real-time. First, all data in the spatial/spectral cube of data is spectro-radiometrically calibrated as it is collected. Second, to allow the imager to simulate sensors with arbitrary spectral response, any set of three spectral response functions may be loaded into the imager including delta functions to allow single wavelength viewing; the instrument then evaluates the integral of the product of the scene spectral radiances and the response function. Third, more powerful exploitation of the gathered spectral radiances can be effected by application of various spectral-matched filtering algorithms to identify pixels whose relative spectral radiance distribution matches a sought-after spectral radiance distribution, allowing materials-based identification and discrimination. Fourth, the instrument allows determination of spectral reflectance, surface temperature, and spectral emissivity, also in real-time. The spectral imaging technique used in the instrument allows tailoring of the frame rate and/or the spectral bandwidth to suit the scene radiance levels, i.e., frame rate can be reduced, or bandwidth increased to improve SNR when viewing low radiance scenes. The unique challenges of design and calibration are described. Pixel readout rates of 160 MHz, for full frame readout rates of 1000 Hz (512 x 512 image) present the first challenge; processing rates of nearly 600 million integer operations per second for sensor emulation, or over 2 billion per second for matched filtering, present the second. Spatial and spectral calibration of 66,536 pixels (262,144 for the 512 x 512 version) and up to 1,000 spectral positions mandate novel decoupling methods to keep the required calibration memory to a reasonable size. Large radiometric dynamic range also requires care to maintain precision operation with minimum memory size.
The present work describes the main considerations and steps taken in determining the functional design of the imaging system of the Mariner Venus/Mercury (MVM) spacecraft and gives examples of some of the interactions between the spacecraft and the imaging instrument during the design and testing phases. Stringent cost and scheduling constraints dictated the use of the previous Mariner 9 dual-camera TV system. The TV parameters laid the groundwork for the imaging definition. Based on the flyby distances from Venus and Mercury and the goal of surface resolution better than 500 meters per sample pair, calculation was performed on focal length, format size, planetary coverage, and data rates. Some problems encountered in initial mechanical operation and as a result of spacecraft drift during the mission are also discussed.
Methods are constructed for rapidly computing correlation functions using the theory of abstract harmonic analysis. The theory developed includes as a particular case the familiar Fourier transform method for a correlation function which makes it possible to find images which are independent of their translation in the plane. Two examples of the application of the general theory described are the search for images, independent of their rotation and scale, and the search for images which are independent of their translations and rotations in the plane.
General ideas of functional statistical inference analysis of one sample and two samples, univariate and bivariate are outlined. ONESAM program is applied to analyze the univariate probability distributions of multi-spectral image data.
Detailed understanding of the properties of the point-spread function (PSF) of Space Telescope Imaging Spectrograph (STIS) imaging modes is necessary to separate real effects of geometrically complex astronomical sources, such as protoplanetary disks surrounding bright stars, from instrumental effects, such as scattering and diffraction. In order to investigate STIS imaging properties we have numerically simulated broadband stellar PSFs generated by STIS in CCD clear imaging mode, including the effects of the Lyot stop and the coronagraphic wedges. The input spectrum is a stellar model atmosphere of the appropriate spectral type, convolved with the pre-flight STIS CCD response function. The PSF modeler generates broadband PSFs by co-adding weighted monochromatic PSFs across the waveband.
The main performance goals for the image sensors are given and the design criteria for accomplishing these goals are discussed. Each functional element of the image sensors is described along with the various tradeoffs considered.
In this paper we describe the optimal image model, maximum residual likelihood method (OptMRL) for image reconstruction. OptMRL is a Bayesian image reconstruction technique for removing point-spread function blurring. OptMRL uses both a goodness-of-fit criterion (GOF) and an 'image prior', i.e., a function which quantifies the a priori probability of the image. Unlike standard maximum entropy methods, which typically reconstruct the image on the data pixel grid, OptMRL varies the image model in order to find the optimal functional basis with which to represent the image. We show how an optimal basis for image representation can be selected and in doing so, develop the concept of the 'pixon' which is a generalized image cell from which this basis is constructed. By allowing both the image and the image representation to be variable, the OptMRL method greatly increases the volume of solution space over which the image is optimized. Hence the likelihood of the final reconstructed image is greatly increased. For the goodness-of-fit criterion, OptMRL uses the maximum residual likelihood probability distribution introduced previously by Pina and Puetter (1992). This GOF probability distribution, which is based on the spatial autocorrelation of the residuals, has the advantage that it ensures spatially uncorrelated image reconstruction residuals.
Blind Iterative Deconvolution (BID) is a technique which was originally developed to correct the degrading effects of atmospheric turbulence on astronomical images from single short exposure, high signal-to-noise-ratio frames. At the Center for Astro physics, we have implemented a version of BID following the general approach of Ayers and Dainty (1988), but extending the technique to use Wiener filtering, and developed it for application to high energy images from Einstein and ROSAT. In the optical, the point spread function (PSF) that degrades the images is due to a combination of telescope and atmospheric aberrations. At high energies, the degrading function is the instrument response function, which is known to be time and energy level unstable. In both cases, the PSF is poorly known, so BID can be used to extract the PSF from the image and then deconvolve the blurred image to produce a sharpened image. Other aspects of this technique are discussed.
The development of interactive image processing techniques which have led to meteorological data processing systems are discussed. Hardware and software functions of the existing Image Display and Manipulation System (IDAMS) and the special-purpose METPAK software package which has been developed for performing meteorology operations on IDAMS are described. A second-generation interactive image processing system, the Atmospheric and Oceanographic Information Processing System (AOIPS), which is under development, is also outlined. These systems are being designed to provide the necessary high throughput required for analysis of geostationary satellite data in the time domain.
The Lightning Imaging Sensor (LIS) wide field-of-view solid-state camera can measure the global distribution of lightning from LEO, through the use of a narrowband interference filter to detect the neutral O band at 777.4 nm. Prelaunch testing and calibration of the LIS has required three separate laboratory systems; absolute radiometric calibration of the sensor will be furnished over the whole spectral range by a high resolution monochromator and motorized gimbals.
Formulations are presented that permit prediction of image quality as a function of camera performance, surface radiance properties, and lighting and viewing geometry. Predictions made for a wide range of surface radiance properties reveal that image quality depends strongly on proper camera dynamic range command and on favorable lighting and viewing geometry. Proper camera dynamic range commands depend mostly on the surface albedo that will be encountered. Favorable lighting and viewing geometries depend mostly on lander orientation with respect to the diurnal sun path over the landing site, and tend to be independent of surface albedo and illumination scattering function. Side lighting with low sun elevation angles (10 to 30 deg) is generally favorable for imaging spatial details and slopes, whereas high sun elevation angles are favorable for measuring spectral reflectances.
Land Analysis System (LAS) is collection of image-analysis computer programs designed to manipulate and analyze multispectral image data. Provides user with functions ingesting various sensor data, radiometric and geometric corrections, image registration, training site selection, supervised and unsupervised classification, Fourier domain filtering, and image enhancement. Sufficiently modular and includes extensive library of subroutines to permit inclusion of new algorithmic programs. Commercial package International Mathematical & Statistical Library (IMSL) required for full implementation of LAS. Written in VAX FORTRAN 77, C, and Macro assembler for DEC VAX operating under VMS 4.0.
An instrument that functions mainly as a particle-image velocimeter provides data on the sizes and velocities of flying opaque particles. The instrument is being developed as a means of characterizing fluxes of wind-borne dust particles in the Martian atmosphere. The instrument could also adapted to terrestrial use in measuring sizes and velocities of opaque particles carried by natural winds and industrial gases. Examples of potential terrestrial applications include monitoring of airborne industrial pollutants and airborne particles in mine shafts. The design of this instrument reflects an observation, made in field research, that airborne dust particles derived from soil and rock are opaque enough to be observable by use of bright field illumination with high contrast for highly accurate measurements of sizes and shapes. The instrument includes a source of collimated light coupled to an afocal beam expander and an imaging array of photodetectors. When dust particles travel through the collimated beam, they cast shadows. The shadows are magnified by the beam expander and relayed to the array of photodetectors. Inasmuch as the images captured by the array are of dust-particle shadows rather of the particles themselves, the depth of field of the instrument can be large: the instrument has a depth of field of about 11 mm, which is larger than the depths of field of prior particle-image velocimeters. The instrument can resolve, and measure the sizes and velocities of, particles having sizes in the approximate range of 1 to 300 m. For slowly moving particles, data from two image frames are used to calculate velocities. For rapidly moving particles, image smear lengths from a single frame are used in conjunction with particle- size measurement data to determine velocities.
When end-users are using multiple satellite images for a study the first step is often the assessment and rectification of geolocation offsets. We have developed an automated algorithm to calculate the geometric offsets between two satellite images. It splits both images into subset images (chips) and resamples them to a common resolution. Offsets are imposed on matching chips and the Pearson Cross Correlation (PCC) value calculated for each offset, where the best PCC gives the true offsets. With the true offsets corrected for, a quality of image registration is calculated, measurement uncertainty (MU). The MU threshold value is non-uniform across sensors because it depends on spectral characteristics of each sensor. Previously, the MU threshold was determined by manual inspection for each new sensor assessed. In this study, we automated MU threshold determination. 1/MU vs calculated offset approximates a Gaussian function in shape, see abstract image. A Gaussian function is fit to this dataset, and the root of the third derivative is calculated and applied as a quality threshold, removing the data of lower quality from the final assessment of image offsets. We apply this algorithm to commercial satellite data for proof of concept.
The functional characteristics and operating requirements of the VICAR (Video Image Communication and Retrieval) system are described. An introduction to the system describes the functional characteristics and the basic theory of operation. A brief description of the data flow as well as tape and disk formats is also presented. A formal presentation of the control statement formats is given along with a guide to usage of the system. The guide provides a step-by-step reference to the creation of a VICAR control card deck. Simple examples are employed to illustrate the various options and the system response thereto.
The VASSIS task was to design and develop an imaging system and container for operation above the surface of Venus in preparation for a Discovery-class mission involving a Venus aerobot balloon. The technical goals of the effort were to: a) evaluate the possible nadir-viewed surface image quality as a function of wavelength and altitude in the Venus lower atmosphere, b) design a pressure vessel to contain the imager and supporting electronics that will meet the environmental requirements of the VASSIS mission, c) design and build a prototype imaging system including an Active-Pixel Sensor camera head and VASSIS-like optics that will meet the science requirements. The VASSIS science team developed a set of science requirements for the imaging system upon which the development work of this task was based.
The functional characteristics and operating requirements of the Video Image Communication and Retrieval System are detailed.