Applications of digital image processing
Digital image processing applied to picture generation, intensity and geometric manipulation, spatial frequency operations and image analysis
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Digital image processing applied to picture generation, intensity and geometric manipulation, spatial frequency operations and image analysis
Parallel image processing which is defined as image processing where all points of an image are operated upon simultaneously is discussed. Coherent optical, noncoherent optical, and electronic methods are considered parallel image processing techniques.
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.
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.
Digital image processing for geological applications will be integrated with geographic information systems and data base management systems. While multiband data sets from radar and multispectral scanners will make extreme demands on memory, bus and processor architectures, it is expected that array processors and VLSI/VHSIC dedicated function chips will allow the use of fast Fourier transform and classification algorithms. It is anticipted that, as processor power increases, the weakest link of a processing system will become the analyst who uses it. Human engineering of systems is therefore recommended for the most effective utilization of remotely sensed geologic data.
An image processing system is the combination of an image processor with other control and display devices plus the necessary software needed to produce an interactive capability to analyze and enhance image data. Such an image processing system installed at NASA Langley Research Center, Instrument Research Division, Acoustics and Vibration Instrumentation Section (AVIS) is described. Although much of the information contained herein can be found in the other references, it is hoped that this single handbook will give the user better access, in concise form, to pertinent information and usage of the image processing system.
The IMAGES interactive image processing system was created specifically for undergraduate remote sensing education in geography. The system is interactive, relatively inexpensive to operate, almost hardware independent, and responsive to numerous users at one time in a time-sharing mode. Most important, it provides a medium whereby theoretical remote sensing principles discussed in lecture may be reinforced in laboratory as students perform computer-assisted image processing. In addition to its use in academic and short course environments, the system has also been used extensively to conduct basic image processing research. The flow of information through the system is discussed including an overview of the programs.
Several techniques of a digital image-processing nature are illustrated which have proved useful in visual analysis of astronomical pictorial data. Processed digital scans of photographic plates of Stephans Quintet and NGC 4151 are used as examples to show how faint nebulosity is enhanced by high-pass filtering, how foreground stars are suppressed by linear interpolation, and how relative color differences between two images recorded on plates with different spectral sensitivities can be revealed by generating ratio images. Analyses are outlined which are intended to compensate partially for the blurring effects of the atmosphere on images of Stephans Quintet and to obtain more detailed information about Saturn's ring structure from low- and high-resolution scans of the planet and its ring system. The employment of a correlation picture to determine the tilt angle of an average spectral line in a low-quality spectrum is demonstrated for a section of the spectrum of Uranus.
Summary Colloidal transport and deposition are of both environmental and engineering importance. Easier access to x‐ray microtomography (XMT) coupled with improved imaging resolution has made XMT a unique and viable tool for visualizing and quantifying these processes. Currently, there is scant information in the literature addressing colloid segmentation and analysis in saturated and unsaturated porous media, in particular related to spatial partitioning of colloids. To support this need, an approach to assign segmented colloidal particles and aggregates to different partitioning classes based on their proximity to different phases is presented here. The method uses different markers for each attachment site (e.g. wetting‐nonwetting phase interfaces). An example XMT dataset from a drainage experiment is used to demonstrate the efficacy of the image processing algorithms. Flow conditions, and fluid and colloid properties, can thus be compared to the behaviour of colloids within the porous medium. This algorithm can help elucidate colloidal deposition mechanisms and the importance of different attachment sites, explore the importance of fluid properties, as well as the arrangement and shape of the colloids.
An existing image processing system is adapted to describe the geologic attributes of a regional coal basin. This scheme handles a map as if it were a matrix, in contrast to more conventional approaches which represent map information in terms of linked polygons. The utility of the image processing approach is demonstrated by a multiattribute analysis of the Herrin No. 6 coal seam in Illinois. Findings include the location of a resource and estimation of tonnage corresponding to constraints on seam thickness, overburden, and Btu value, which are illustrative of the need for new mining technology.
Imaging spectrometers simultaneously collect image data in hundreds of spectral channels, from the near-UV to the IR, and can thereby provide direct surface materials identification by means resembling laboratory reflectance spectroscopy. Attention is presently given to a software system, the Spectral Analysis Manager (SPAM) for the analysis of imaging spectrometer data. SPAM requires only modest computational resources and is composed of one main routine and a set of subroutine libraries. Additions and modifications are relatively easy, and special-purpose algorithms have been incorporated that are tailored to geological applications.
The paper presents a software system, Spectral Analysis Manager (SPAM), which has been specifically designed and implemented to provide the exploratory analysis tools necessary for imaging spectrometer data, using only modest computational resources. The basic design objectives are described as well as the major algorithms designed or adapted for high-dimensional images. Included in a discussion of system implementation are interactive data display, statistical analysis, image segmentation and spectral matching, and mixture analysis.
An array processing chip integrating 128 bit-serial processing elements (PEs) on a single die is discussed. Each PE has a 16-function logic unit, a single-bit adder, a 32-b variable-length shift register, and 1 kb of local RAM. Logic in each PE provides the capability to mask PEs individually. A modified grid interconnection scheme allows each PE to communicate with each of its eight nearest neighbors. A 32-b bus is used to transfer data to and from the array in a single cycle. Instruction execution is pipelined, enabling all instructions to be executed in a single cycle. The 1-micron CMOS design contains over 1.1 x 10 to the 6th transistors on an 11.0 x 11.7-mm die.
Abstract not provided.
Apple Image-Processing Educator (AIPE) explores ability of microcomputers to provide personalized computer-assisted instruction (CAI) in digital image processing of remotely sensed images. AIPE is "proof-of-concept" system, not polished production system. User-friendly prompts provide access to explanations of common features of digital image processing and of sample programs that implement these features.
The Vera C. Rubin Observatory is preparing to execute the most ambitious astronomical survey ever attempted, the Legacy Survey of Space and Time (LSST). Currently the final phase of construction is under way in the Chilean Andes, with the Observatory’s ten-year science mission scheduled to begin in 2025. Rubin’s 8.4-meter telescope will nightly scan the southern hemisphere collecting imagery in the wavelength range 320–1050 nm covering the entire observable sky every 4 nights using a 3.2 gigapixel camera, the largest imaging device ever built for astronomy. Automated detection and classification of celestial objects will be performed by sophisticated algorithms on high-resolution images to progressively produce an astronomical catalog eventually composed of 20 billion galaxies and 17 billion stars and their associated physical properties. In this article we present an overview of the system currently being constructed to perform data distribution as well as the annual campaigns which reprocess the entire image dataset collected since the beginning of the survey. These processing campaigns will utilize computing and storage resources provided by three Rubin data facilities (one in the US and two in Europe). Each year a Data Release will be produced and disseminated to science collaborations for use in studies comprising four main science pillars: probing dark matter and dark energy, taking inventory of solar system objects, exploring the transient optical sky and mapping the Milky Way. Also presented is the method by which we leverage some of the common tools and best practices used for management of large-scale distributed data processing projects in the high energy physics and astronomy communities. We also demonstrate how these tools and practices are utilized within the Rubin project in order to overcome the specific challenges faced by the Observatory.
Digital image processing techniques for correction of ERTS-1 image data
ERTS-1 MSS and RBV data recorded on computer compatible tapes have been analyzed and processed, and preliminary results have been obtained. No degradation of intensity (radiance) information occurred in implementing the geometric correction. The quality and resolution of the digitally processed images are very good, due primarily to the fact that the number of film generations and conversions is reduced to a minimum. Processing times of digitally processed images are about equivalent to the NDPF electro-optical processor.