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At least 19 records

Subroutines For Image Processing

Image Processing Library computer program, IPLIB, is collection of subroutines facilitating use of COMTAL image-processing system driven by HP 1000 computer. Functions include addition or subtraction of two images with or without scaling, display of color or monochrome images, digitization of image from television camera, display of test pattern, manipulation of bits, and clearing of screen. Provides capability to read or write points, lines, and pixels from image; read or write at location of cursor; and read or write array of integers into COMTAL memory. Written in FORTRAN 77.

Faulcon, Nettie D.↗

Enhancement of structure images of interstellar diamond microcrystals by image processing

Image processed high resolution TEM images of diamond crystals found in oxidized acid residues of carbonaceous chondrites are presented. Two models of the origin of the diamonds are discussed. The model proposed by Lewis et al. (1987) supposes that the diamonds formed under low pressure conditions, whereas that of Blake et al (1988) suggests that the diamonds formed due to particle-particle collisions behind supernova shock waves. The TEM images of the diamond presented support the high pressure model.

O'Keefe, Michael A.↗

Voyager image processing at the Image Processing Laboratory

This paper discusses new digital processing techniques as applied to the Voyager Imaging Subsystem and devised to explore atmospheric dynamics, spectral variations, and the morphology of Jupiter, Saturn and their satellites. Radiometric and geometric decalibration processes, the modulation transfer function, and processes to determine and remove photometric properties of the atmosphere and surface of Jupiter and its satellites are examined. It is exhibited that selected images can be processed into 'approach at constant longitude' time lapse movies which are useful in observing atmospheric changes of Jupiter. Photographs are included to illustrate various image processing techniques.

Jepsen, P. L.↗

Combining image-processing and image compression schemes

An investigation into the combining of image-processing schemes, specifically an image enhancement scheme, with existing compression schemes is discussed. Results are presented on the pyramid coding scheme, the subband coding scheme, and progressive transmission. Encouraging results are demonstrated for the combination of image enhancement and pyramid image coding schemes, especially at low bit rates. Adding the enhancement scheme to progressive image transmission allows enhanced visual perception at low resolutions. In addition, further progressing of the transmitted images, such as edge detection schemes, can gain from the added image resolution via the enhancement.

Greenspan, H.↗

Recent Advances in Techniques for Hyperspectral Image Processing

Imaging spectroscopy, also known as hyperspectral imaging, has been transformed in less than 30 years from being a sparse research tool into a commodity product available to a broad user community. Currently, there is a need for standardized data processing techniques able to take into account the special properties of hyperspectral data. In this paper, we provide a seminal view on recent advances in techniques for hyperspectral image processing. Our main focus is on the design of techniques able to deal with the highdimensional nature of the data, and to integrate the spatial and spectral information. Performance of the discussed techniques is evaluated in different analysis scenarios. To satisfy time-critical constraints in specific applications, we also develop efficient parallel implementations of some of the discussed algorithms. Combined, these parts provide an excellent snapshot of the state-of-the-art in those areas, and offer a thoughtful perspective on future potentials and emerging challenges in the design of robust hyperspectral imaging algorithms

Plaza, Antonio↗

Image Processing

Images are prepared from data acquired by the multispectral scanner aboard Landsat, which views Earth in four ranges of the electromagnetic spectrum, two visible bands and two infrared. Scanner picks up radiation from ground objects and converts the radiation signatures to digital signals, which are relayed to Earth and recorded on tape. Each tape contains "pixels" or picture elements covering a ground area; computerized equipment processes the tapes and plots each pixel, line be line to produce the basic image. Image can be further processed to correct sensor errors, to heighten contrast for feature emphasis or to enhance the end product in other ways. Key factor in conversion of digital data to visual form is precision of processing equipment. Jet Propulsion Laboratory prepared a digital mosaic that was plotted and enhanced by Optronics International, Inc. by use of the company's C-4300 Colorwrite, a high precision, high speed system which manipulates and analyzes digital data and presents it in visual form on film. Optronics manufactures a complete family of image enhancement processing systems to meet all users' needs. Enhanced imagery is useful to geologists, hydrologists, land use planners, agricultural specialists geographers and others.

Source record↗

IBIS - A geographic information system based on digital image processing and image raster datatype

IBIS (Image Based Information System) is a geographic information system which makes use of digital image processing techniques to interface existing geocoded data sets and information management systems with thematic maps and remotely sensed imagery. The basic premise is that geocoded data sets can be referenced to a raster scan that is equivalent to a grid cell data set. The first applications (St. Tammany Parish, Louisiana, and Los Angeles County) have been restricted to the design of a land resource inventory and analysis system. It is thought that the algorithms and the hardware interfaces developed will be readily applicable to other Landsat imagery.

Bryant, N. A.↗

APPLEPIPS /Apple Personal Image Processing System/ - An interactive digital image processing system for the Apple II microcomputer

Recent developments related to microprocessor-based personal computers have made low-cost digital image processing systems a reality. Image analysis systems built around these microcomputers provide color image displays for images as large as 256 by 240 pixels in sixteen colors. Descriptive statistics can be computed for portions of an image, and supervised image classification can be obtained. The systems support Basic, Fortran, Pascal, and assembler language. A description is provided of a system which is representative of the new microprocessor-based image processing systems currently on the market. While small systems may never be truly independent of larger mainframes, because they lack 9-track tape drives, the independent processing power of the microcomputers will help alleviate some of the turn-around time problems associated with image analysis and display on the larger multiuser systems.

Masuoka, E.↗

Low level image processing techniques using the pipeline image processing engine in the flight telerobotic servicer

The sensory processing system for the NASA/NBS Standard Reference Model (NASREM) for telerobotic control is described. This control system architecture was adopted by NASA of the Flight Telerobotic Servicer. The control system is hierarchically designed and consists of three parallel systems: task decomposition, world modeling, and sensory processing. The Sensory Processing System is examined, and in particular the image processing hardware and software used to extract features at low levels of sensory processing for tasks representative of those envisioned for the Space Station such as assembly and maintenance are described.

Nashman, Marilyn↗

Experimental study on flow characterization of a rectangular spouted bed by image processing

Systematic image processing methods are applied to characterize gas-solid flow under different operating conditions in a 30.2 mm x 101.6 mm rectangular spouted bed. Geldart D particles are imaged using a highspeed video camera. Superficial gas velocity, initial bed height, and nozzle size are investigated as influence factors. By applying adaptive thresholding and logical operation to the video frames, the original color images are transformed into binary images exposing detailed boundary information. By analyzing the binary image using a self-developed algorithm in combination with mask operations, the bed height is successfully determined, through which the variation of the bed expansion ratio with superficial gas velocity can be obtained. Additionally, the application of image morphological operations, i.e. dilation and erosion on the binarized images ensures the accurate identification of the contours of the jet and fountain so that the jet and fountain heights can be determined. Based on the image processing methods, the variation of bed expansion ratio, jet height and fountain height with the three influence factors are discussed. The current study highlights the application of image analysis in investigating the flow characterization and obtaining more hydrodynamic information in a rectangular spouted bed.

42 ENGINEERING↗

A new programming metaphor for image processing procedures

Most image processing systems, besides an Application Program Interface (API) which lets users write their own image processing programs, also feature a higher level of programmability. Traditionally, this is a command or macro language, which can be used to build large procedures (scripts) out of simple programs or commands. This approach, a legacy of the teletypewriter has serious drawbacks. A command language is clumsy when (and if! it attempts to utilize the capabilities of a multitasking or multiprocessor environment, it is but adequate for real-time data acquisition and processing, it has a fairly steep learning curve, and the user interface is very inefficient,. especially when compared to a graphical user interface (GUI) that systems running under Xll or Windows should otherwise be able to provide. ll these difficulties stem from one basic problem: a command language is not a natural metaphor for an image processing procedure. A more natural metaphor - an image processing factory is described in detail. A factory is a set of programs (applications) that execute separate operations on images, connected by pipes that carry data (images and parameters) between them. The programs function concurrently, processing images as they arrive along pipes, and querying the user for whatever other input they need. From the user's point of view, programming (constructing) factories is a lot like playing with LEGO blocks - much more intuitive than writing scripts. Focus is on some of the difficulties of implementing factory support, most notably the design of an appropriate API. It also shows that factories retain all the functionality of a command language (including loops and conditional branches), while suffering from none of the drawbacks outlined above. Other benefits of factory programming include self-tuning factories and the process of encapsulation, which lets a factory take the shape of a standard application both from the system and the user's point of view, and thus be used as a component of other factories. A bare-bones prototype of factory programming was implemented under the PcIPS image processing system, and a complete version (on a multitasking platform) is under development.

Smirnov, O. M.↗

Process Image Analysis using Big Data, Machine Learning, and Computer Vision

Within the DOE complex, 3013 canisters are used to store Pu-bearing waste. Wall penetration due to corrosion, specifically stress corrosion cracking, is considered to be the most likely cause of failure over the 50-year lifetime of the canisters. This project has 2 objectives: The first is the development of machine learning algorithms to identify the presence of corrosion from a very large set of images generated by laser confocal microscope scanning of 3013 canister used to store Pu oxides. This portion of the LDRD constitutes image analysis of a metal surface for the presence of corrosion. The image processing algorithms developed for this project will provide a suitable basis for analysis of other types of corrosion data, which can be produced in vast quantities using modern devices. The second component of the LDRD consists of the development of machine learning algorithms that obtain molecular mechanics force-fields from ab-initio Density Functional Theory (DFT) calculations for corrosive attack by chlorides on 304L or 316L stainless steel. The goal of this latter component is to determine means for mitigating corrosion on a fundamental level, including coatings, welding methods, metal composition, etc. Force-field modeling is necessary for this endeavor because the incipience and progression of corrosion is the governed by molecular structures, grain boundaries, dislocations and surface structures represented by large numbers of atoms. Although DFT calculations are extremely adept at describing molecular scale processes, they are computationally expensive making them ill-suited for calculations of more than several hundred atoms, especially for the repeated applications inherent in material design. Fortunately, force-field methods provide an avenue for viable molecular-scale calculations involving the numbers of atoms involved in corrosion processes. The accuracy of the force-field calculations depends strongly on the accuracy of the force-field model, which is extremely difficult and time-consuming to derive from either data or ab-initio calculations. The use of machine learning algorithms has the potential to make the calculation of force-fields much more efficient but has not been explored significantly for corrosion processes. If shown to be viable, the technique would have wide -ranging impact on design of corrosion resistant materials and on the mitigation of corrosion in existing process systems.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Applications of digital image processing

Digital image processing applied to picture generation, intensity and geometric manipulation, spatial frequency operations and image analysis

Billingsley, F. C.↗

Review of image processing fundamentals

Image processing through convolution, transform coding, spatial frequency alterations, sampling, and interpolation are considered. It is postulated that convolution in one domain (real or frequency) is equivalent to multiplication in the other (frequency or real), and that the relative amplitudes of the Fourier components must be retained to reproduce any waveshape. It is suggested that all digital systems may be considered equivalent, with a frequency content approximately at the Nyquist limit, and with a Gaussian frequency response. An optimized cubic version of the interpolation continuum image is derived as a set of cubic spines. Pixel replication has been employed to enlarge the visable area of digital samples, however, suitable elimination of the extraneous high frequencies involved in the visable edges, by defocusing, is necessary to allow the underlying object represented by the data values to be seen.

Billingsley, F. C.↗

The application of high density tape recording to image processing

The Image Processing Facility at Goddard Space Flight Center has the requirement to move volumes of digital data (100 billion data bits per day) that exceed the capacity of conventional computer tape. This paper presents the requirements for a high-density digital tape recorder compatible with conventional computer systems. The steps leading to the formulation of these requirements are described. The use and interaction of the recorder with the various elements in the facility are treated. The formulation of the requirements resulted in the selection of a tape transport modified for digital serial-in, serial-out operation. This selection followed a competitive procurement action.

Heffner, P.↗