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The Optical Navigation System for Orion has been developed to ensure that the crew can return safely to Earth in case of a loss of communications. This presentation contains an overview of the image processing aspect of the Orion optical navigation system. The top level architecture is presented along with results of the testing of these image processing system.
A PC based image processing system was employed to determine the instantaneous velocity field of a two-dimensional unsteady flow. The flow was visualized using a suspension of seeding particles in water, and a laser sheet for illumination. With a finite time exposure, the particle motion was captured on a photograph as a pattern of streaks. The streak pattern was digitized and processsed using various imaging operations, including contrast manipulation, noise cleaning, filtering, statistical differencing, and thresholding. Information concerning the velocity was extracted from the enhanced image by measuring the length and orientation of the individual streaks. The fluid velocities deduced from the randomly distributed particle streaks were interpolated to obtain velocities at uniform grid points. For the interpolation a simple convolution technique with an adaptive Gaussian window was used. The results are compared with a numerical prediction by a Navier-Stokes commputation.
Three image processing experiments were performed by degenerate four-wave mixing in photorefractive GaAs. The experiments were imaging by phase conjugation, edge enhancement, and autocorrelation. The results show that undoped, semiinsulating, liquid-encapsulated Czochralski-grown GaAs crystals can be used as effective optical processing media despite their small electrooptic coefficient.
A real-time synthetic aperture radar (SAR) image processing architecture amenable to future on-board spacecraft applications is currently under development. Using state-of-the-art charge-coupled device (CCD) technology, low cost and power are inherent features. Other characteristics include the ability to reprogram correlation reference functions, correct for range migration, and compensate for antenna beam pointing errors on the spacecraft in real time. The first spaceborne demonstration is scheduled to be flown as an experiment on a 1982 Shuttle imaging radar mission (SIR-B). This paper describes the architecture and implementation characteristics of this initial spaceborne CCD SAR image processor.
Low-cost vector processing (VP) is within reach of everyone seriously engaged in scientific computing. The advent of affordable add-on VP-boards for standard workstations complemented by mathematical/statistical libraries is beginning to impact compute-intensive tasks such as image processing. A case in point in the restoration of distorted images from the Hubble Space Telescope. A low-cost implementation is presented of the standard Tarasko-Richardson-Lucy restoration algorithm on an Intel i860-based VP-board which is seamlessly interfaced to a commercial, interactive image processing system. First experience is reported (including some benchmarks for standalone FFT's) and some conclusions are drawn.
Walsh functions in image processing, rotational feature selection and pattern recognition, defining set of orthogonal transformations
Techniques for using image processing in astronomy are identified and developed for the following: (1) geometric and radiometric decalibration of vidicon-acquired spectra, (2) automatic identification and segregation of stars from galaxies; and (3) display of multiband radio maps in compact and meaningful formats. Examples are presented of these techniques applied to a variety of objects.
Digital imaging techniques used in sinusoidal frequency response modification with or without computer control and display on operator console
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.
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.
This paper describes digital image processing techniques that were developed to precisely correct Landsat multispectral earth observation data and gives illustrations of the results achieved, e.g., geometric corrections with an error of less than one picture element, a relative error of one-fourth picture element, and no radiometric error effect. Techniques for enhancing the sensor data, digitally mosaicking multiple scenes, and extracting information are also illustrated.
The utility of cluster computers (Beowulfs) for efficient parallel image processing of large-scale mosaics and stereo image correlations is presented.
CIPE (the Concurrent Image Processing Executive) is both an executive which organizes the parameter inputs for hypercube applications and an environment which provides temporary data workspace and simple real-time function definition facilities for image analysis. CIPE provides two types of user interface. The Command Line Interface (CLI) provides a simple command-driven environment allowing interactive function definition and evaluation of algebraic expressions. The menu interface employs a hierarchical screen-oriented menu system where the user is led through a menu tree to any specific application and then given a formatted panel screen for parameter entry. How to initialize the system through the setup function, how to read data into CIPE symbols, how to manipulate and display data through the use of executive functions, and how to run an application in either user interface mode, are described.
The present paper describes several software techniques that can be used to get the 'most' out of an image without destroying or adding any information. A simple overview is given of a general image-processing system, a number of systems in current use are listed, and three types of processing tasks are delineated: image diagnostics, subjective enhancement, and quantitative restoration. Examples of each of these types are discussed in some detail, including histogram, differences, and Fourier analysis for image diagnostics; contrast stretching, edge enhancement, and pseudocolor displays for subjective enhancement; and photometric correction, contouring, and geometric correction for quantitative restoration.
The development of a digital image processing system for bone histomorphometry and fluorescent marker monitoring is discussed. The system in question is capable of making measurements of UV or light microscope features on a video screen with either video or computer-generated images, and comprises a microscope, low-light-level video camera, video digitizer and display terminal, color monitor, and PDP 11/34 computer. Capabilities demonstrated in the analysis of an undecalcified rat tibia include the measurement of perimeter and total bone area, and the generation of microscope images, false color images, digitized images and contoured images for further analysis. Software development will be based on an existing software library, specifically the mini-VICAR system developed at JPL. It is noted that the potentials of the system in terms of speed and reliability far exceed any problems associated with hardware and software development.
A systematic introduction to the concepts and techniques of computer image processing and recognition is presented. Consideration is given to such topics as image formation and perception; computer representation of images; image enhancement and restoration; reconstruction from projections; digital television, encoding, and data compression; scene understanding; scene matching and recognition; and processing techniques for linear systems.
Several areas of applications of image processing to astronomy were identified and discussed. These areas include: (1) deconvolution for atmospheric seeing compensation; a comparison between maximum entropy and conventional Wiener algorithms; (2) polarization in galaxies from photographic plates; (3) time changes in M87 and methods of displaying these changes; (4) comparing emission line images in planetary nebulae; and (5) log intensity, hue saturation intensity, and principal component color enhancements of M82. Examples are presented of these techniques applied to a variety of objects.
Advanced manufacturing (AM) processes such as laser powder bed fusion (LPBF) are increasingly capable of fabricating components with useful and unprecedented mechanical properties by incorporating complex internal bracing structures. From the standpoint of quality control and assessment, however, internally complex assemblies present significant build-verification challenges. Here we propose a hybrid approach to the inspection involving the application of computer-aided speckle interferometry (CASI) and morphological image processing as a rapid, inexpensive, and facile method for AM quality control. The described methodology has low capital equipment costs, is full-field and non-contact, can be used in an industrial setting, and has very low requirements in terms of operator training and expertise. Consisting primarily of the combination of image processing software with a simple optical system of variable sensitivity, the method is shown to be effective for inspection of a titanium honeycomb component subjected to differential pressure. Results are compared to those achieved with computed tomography (CT), immersion ultrasound testing (UT), and optical holographic interferometry. Here we propose several possible processing strategies for automated quality assessment based on this powerful hybrid approach.