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A system is described which allows for the synthesis of a video sequence of a realistic-appearing talking human head. A phonic based approach is used to describe facial motion; image processing rather than physical modeling techniques are used to create video frames.
Some of the imaging problems encountered in space-borne X-ray astronomy are reviewed, along with the techniques considered for their solution. Following a discussion of X-ray focussing and X-ray image processing, the development of X-ray imaging devices is surveyed. It is shown that the imaging devices that will be used in X-ray astronomy will take advantage of developments intended for infrared and optical astronomy. The special requirements of X-ray observation - especially, single photon detection and high time resolution - rule out the use of existing devices, particularly because of readout problems.
The constraints that are imposed on the Outer Planet Missions (OPM) imager design are of critical importance. Imager system modeling analyses define important parameters and systematic means for trade-offs applied to specific Jupiter orbiter missions. Possible image sequence plans for Jupiter missions are discussed in detail. Considered is a series of orbits that allow repeated near encounters with three of the Jovian satellites. The data handling involved in the image processing is discussed, and it is shown that only minimal processing is required for the majority of images for a Jupiter orbiter mission.
Special test equipment and techniques to collect and process image information from charge coupled devices (CCDs) by digital computer were reviewed. The video channel was traced from the CCD to the direct memory access bus of the Interdata Computer. Software was developed to evaluate and characterize a CCD for (1) dark signal versus temperature relationship, (2) calculation of temporal noise magnitude and noise shape for each pixel, (3) spatial noise into the video chain due to dark signal, (4) response versus illumination relationship (gamma), (5) response versus wavelength of illumination (spectral), (6) optimization of forcing functions, and (7) evaluation of an image viewed by a CCD. The basic software differences and specific examples of each program operating on real data are presented.
Optical and optical electronic hybrid processing especially in the application area of image processing are emphasized. Real time pattern recognition processors for such airborne missions as target recognition, tracking, and terminal guidance are studied.
A near-infrared array camera system has been constructed for use in the 1-5 micron region. The camera is based on a 32 x 32 element InSb focal plane array. The performance of most of the individual detectors in the system is found to be comparable to or better than the performance of any single-element InSb detector system currently in use. A thorough description of the camera system and its image processing subsystems is given, and some sample images are provided.
A laboratory for developing robotics technology for hazardous and repetitive Shuttle and payload processing activities is discussed. An overview of the computer hardware and software responsible for integrating the laboratory systems is given. The center's anthropomorphic robot is placed on a track allowing it to be moved to different stations. Various aspects of the laboratory equipment are described, including industrial robot arm control, smart systems integration, the supervisory computer, programmable process controller, real-time tracking controller, image processing hardware, and control display graphics. Topics of research include: automated loading and unloading of hypergolics for space vehicles and payloads; the use of mobile robotics for security, fire fighting, and hazardous spill operations; nondestructive testing for SRB joint and seal verification; Shuttle Orbiter radiator damage inspection; and Orbiter contour measurements. The possibility of expanding the laboratory in the future is examined.
The intent is to present an effort undertaken at NASA Langley Research Center to design a generic raster image format and to develop tools for processing images prepared in this format. Both the Raster Metafile (RM) format and the Raster Metafile Translator (RMT) are addressed. This document is intended to serve a varied audience including: users wishing to display and manipulate raster image data, programmers responsible for either interfacing the RM format with other raster formats or for developing new RMT device drivers, and programmers charged with installing the software on a host platform.
This paper presents initial flight results for angles-only navigation of a swarm of small spacecraft, conducted during the Starling Formation-Flying Optical Experiment (StarFOX). StarFOX is one of four experiments aboard the NASA Starling mission, which consists of four CubeSats launched in July 2023. Angles-only methods apply inter-satellite bearing angles obtained by on-board cameras for navigation, increasing satellite autonomy and enabling new mission concepts. Nevertheless, prior flight demonstrations have only featured one observer and target and have relied upon a-priori target orbit knowledge for initialization, translational maneuvers to resolve target range, and external absolute orbit updates to maintain convergence. StarFOX overcomes these limitations by applying the angles-only Absolute and Relative Trajectory Measurement System (ARTMS), which integrates three novel algorithms. Image Processing detects and tracks multiple targets in images, using multi-hypothesis methods and domain-specific kinematic modeling, and computes target bearing angles. Batch Orbit Determination computes initial swarm orbit estimates from bearing angle batches, via iterative batch least squares and sampling of the weakly observable target range. Sequential Orbit Determination leverages an adaptive, efficient unscented Kalman filter with nonlinear models to refine swarm state estimates over time. Multi-observer measurements shared over an intersatellite link are seamlessly fused to enable robust absolute and relative orbit determination. Initial StarFOX experiments are the first demonstrations of autonomous angles-only navigation for a satellite swarm, including multi-target and multi-observer relative navigation; autonomous initialization of navigation for unknown targets; and simultaneous absolute and relative orbit determination. Relative navigation accuracy of 1% (single observer) and 0.2% (multi-observer) of the inter-satellite range is achieved under challenging measurement conditions. Results demonstrate promising performance with regards to ongoing StarFOX campaigns and the application of angles-only navigation to future distributed missions.
Noise in magneto-optical recording devices is discussed. In general, it appears that either the divider technique or amplitude spectrum technique may be used interchangeably to measure the fractal dimension (D) in the domain wall structure of ideal images. However, some caveats must be observed for best results. The divider technique is attractive for its simplicity and relatively modest computation requirements. However, it is sensitive to noise, in that noise pixels that touch the domain boundary are interpreted as being part of the boundary, skewing the measurement. Also, it is not useful in measuring nucleation-dominated films or domains that have significant amounts of structure within the interior of the domain wall. The amplitude spectrum method is more complex, and less intuitive than the divider method, and somewhat more expensive to implement computationally. However, since the camera noise tends to be white, the noise can be avoided in the measurement of D by avoiding that portion of the curve that is flat (due to the white noise) when the least squares line is fit to the plot. Also, many image processing software packages include a Fast Fourier Transformation (FFT) facility, while the user will most likely have to write his own edge extraction routine for the divider method. The amplitude spectrum method is a true two dimensional technique that probes the interior of the domain wall, and in fact, can measure arbitrary clusters of domains. It can also be used to measure grey-level images, further reducing processing steps needed to threshold the image.
In order to overcome spatial resolution limitations associated with physical sensor limitations when using smallsats and cubesats, we utilize an image processing technology referred to as Super-Resolution (SR). In general, software approaches are increasingly considered in connection with smaller satellites for which size, mass and power constraints limit the sensor capabilities. Being able to perform hardware vs. software trades might enable more capabilities for a lower cost. This paper describes recent experiments conducted to optimize the spatial enhancement of acquired observations using multiple sub-pixel shifted low resolution image.
In order to overcome spatial resolution limitations associated with physical sensor limitations when using smallsats and cubesats, we utilize an image processing technology referred to as Super-Resolution (SR). In general, software approaches are increasingly considered in connection with smaller satellites for which size, mass and power constraints limit the sensor capabilities. Being able to perform hardware vs. software trades might enable more capabilities for a lower cost. This paper describes recent experiments conducted to optimize the spatial enhancement of acquired observations using multiple sub-pixel shifted low resolution image.
Over 1000 camera events were returned from the two Viking landers during the Primary Mission. A system was devised for processing camera data as they were received, in real time, from the Deep Space Network. This system provided a flexible choice of parameters for three computer-enhanced versions of the data for display or hard-copy generation. Software systems allowed all but 0.3% of the imagery scan lines received on earth to be placed correctly in the camera data record. A second-order processing system was developed which allowed extensive interactive image processing including computer-assisted photogrammetry, a variety of geometric and photometric transformations, mosaicking, and color balancing using six different filtered images of a common scene. These results have been completely cataloged and documented to produce an Experiment Data Record.
The advanced inspection system is an autonomous control and analysis system that improves the inspection and remediation operations for ground and surface systems. It uses optical imaging technology with intelligent computer vision algorithms to analyze physical features of the real-world environment to make decisions and learn from experience. The advanced inspection system plans to control a robotic manipulator arm, an unmanned ground vehicle and cameras remotely, automatically and autonomously. There are many computer vision, image processing and machine learning techniques available as open source for using vision as a sensory feedback in decision-making and autonomous robotic movement. My responsibilities for the advanced inspection system are to create a software architecture that integrates and provides a framework for all the different subsystem components; identify open-source algorithms and techniques; and integrate robot hardware.
Retinex Imaging Processing, winner of NASA's 1999 Space Act Award, is commercially available through TruView Imaging Company. With this technology, amateur photographers use their personal computers to improve the brightness, scene contrast, detail, and overall sharpness of images with increased ease. The process was originally developed for remote sensing of the Earth by researchers at Langley Research Center and Science and Technology Corporation (STC). It automatically enhances a digital image in terms of dynamic range compression, color independence from the spectral distribution of the scene illuminant, and color/lightness rendition. As a result, the enhanced digital image is much closer to the scene perceived by the human visual system, under all kinds and levels of lighting variations. TruView believes there are other applications for the software in medical imaging, forensics, security, recognizance, mining, assembly, and other industrial areas.
A vectorized rebinning (down-sampling) algorithm, applicable to N-dimensional data sets, has been developed that offers a significant reduction in computer run time when compared to conventional rebinning algorithms. For clarity, a two-dimensional version of the algorithm is discussed to illustrate some specific details of the algorithm content, and using the language of image processing, 2D data will be referred to as "images," and each value in an image as a "pixel." The new approach is fully vectorized, i.e., the down-sampling procedure is done as a single step over all image rows, and then as a single step over all image columns. Data rebinning (or down-sampling) is a procedure that uses a discretely sampled N-dimensional data set to create a representation of the same data, but with fewer discrete samples. Such data down-sampling is fundamental to digital signal processing, e.g., for data compression applications.
The application of the VAS program is outlined. The initial assessments of VAS radiometer and satellite performance were satisfactory; and VAS operations were smoothly carried out by the NESS SOCC and associated processing and retransmission facilities. The availability of advanced image processing systems, previous studies with the geosynchronous European Space Agency Meteorological Satellite (Meteosat), and the polar orbiter multichannel radiance data enabled the progress of the application. The VAS data are implemented as these data are received in the real time VISSR mode, and as dwell sounding (DS) and multispectral imaging (MSI) radiances on magnetic tapes.
Radiometric accuracy of ERTS photographic image processing is assured by the use of control targets, i.e., sensitometric strips for equipment certification and end-of-roll targets for process verification. These targets are produced by a sensitometer that is calibrated to cover the performance range parameters. Curve fitting techniques are used to collect performance data accurately, and a feedback procedure indicates malfunctioning.