Preprocessing of Minitrack data
Minitrack data reduction procedures, with IBM 360 computer program description
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Minitrack data reduction procedures, with IBM 360 computer program description
A noncritical empirical detail-by-detail transformation of environmental information into flight display by purely physical methods characterizes the textured visual simulation as indiscernibly identical with the real scene. This method uses image storage, readout, image transformation, and graphic display to present a true color visual flight image to the pilot onboard aircraft in a purely electronic manner, employing analog-hybrid techniques.
There are no author-identified significant results in this report.
Frequency bands that best discriminate the Korotkov sounds at systole and at diastole from the sounds immediately preceding these events are defined. Korotkov sound data were recorded from five normotensive subjects during orthostatic stress (lower body negative pressure) and bicycle ergometry. A spectral analysis of the seven Korotkov sounds centered about the systolic and diastolic auscultatory events revealed that a maximum increase in amplitude at the systolic transition occurred in the 18-26-Hz band, while a maximum decrease in amplitude at the diastolic transition occurred in the 40-60-Hz band. These findings were remarkably consistent across subjects and test conditions. These passbands are included in the design specifications for an automatic blood pressure measuring system used in conjuction with medical experiments during NASA's Skylab program.
There are no author-identified significant results in this report.
A basic concept of Multispectral Scanner data processing was developed for use in agricultural inventories; namely, to introduce spatial coordinates of each pixel into the vector description of the pixel and to use this information along with the spectral channel values in a conventional unsupervised clustering of the scene. The result is to isolate spectrally homogeneous field-like patches (called blobs). The spectral mean vector of a blob can be regarded as a defined feature and used in a conventional pattern recognition procedure. The benefits of use are: ease in locating training units in imagery; data compression of from 10 to 30 depending on the application; reduction of scanner noise and consequently potential improvements in classification/proportion estimation performances.
A basic concept of MSS data processing has been developed for use in agricultural inventories; namely, to introduce spatial coordinates of each pixel into the vector description of the pixel and to use this information along with the spectral channel values in a conventional unsupervised clustering of the scene. The result is to isolate spectrally homogeneous field-like patches (called 'blobs'). The spectral mean vector of a blob can be regarded as a defined feature and used in a conventional pattern recognition procedure. The benefits of use are: ease in locating training units in imagery; data compression of from 10 to 30 depending on the application; reduction of scanner noise and consequently potential improvements in classification/proportion estimation performances.
The development of airborne and satellite multispectral image scanning sensors has generated wide-spread interest in application of these sensors to earth resource mapping. These point scanning sensors permit scenes to be imaged in a large number of electromagnetic energy bands between .3 and 15 micrometers. The energy sensed in each band can be used as a feature in a computer based multi-dimensional pattern recognition process to aid in interpreting the nature of elements in the scene. Images from each band can also be interpreted visually. Visual interpretation of five or ten multispectral images simultaneously becomes impractical especially as area studied increases; hence, great emphasis has been placed on machine (computer) techniques for aiding in the interpretation process. This paper describes a computer software system concept called LARSYS for analysis of multivariate image data and presents some examples of its application.
A processing system is presented that implements simultaneously the efficiency of the special-purpose processor and the total applicability of the general-purpose computer - characteristics commonly thought of as being mutually exclusive. The solution adopted is that of specializing the machine by programming the hardware structure, rather than by adding software systems to it. Data are organized in circulating pages which form a plurality of local dynamic memories for each process. Programs are made up of modules, each describing a transient special-purpose machine. Applications to real-time processing of radar signals are referred to.
There are no author-identified significant results in this report.
There are no author-identified significant results in this report.
There are no author-identified significant results in this report.
There are no author-identified significant results in this report.
There are no author-identified significant results in this report.
A description is presented of the fabrication of a new InSb CCD chip based on an improved process which eliminates the limitations inherent with the earlier techniques. This process includes planar junction formation and an aluminum and SiO2 material system which is amenable to state-of-the-art chemical and plasma delineation techniques. Further, the new chip integrates for the first time in monolithic format InSb IR detectors with an InSb CCD. The reported experiments represent the first operation of an InSb infrared CCD array. In addition to fuller characterization of the 20-element charge-coupled infrared imaging device, several factors which influence device performance are currently being addressed. These include surface state density, the CCD output circuit, and storage time (dark current).
Two computer algorithms are presented. The first, called SCREEN, is used to automatically identify pixels representing clouds, cloud shadows, snow, water, or anomalous signals in Landsat-2 data. The second, called XSTAR, compensates Landsat-2 data for the effects of atmospheric haze, without requiring ground measurements or ground references. The presentation of these algorithms includes their theoretical background, algebraic details, and performance characteristics. Verification of the algorithms has for the present been limited to Landsat agricultural data. Plans for further development of the XSTAR technique are also presented.
There are no author-identified significant results in this report.
A program that was undertaken to design, fabricate, and test a real-time hardwired data preprocessor is described, which applies a calibration normalization to each detector in a 576-element linear photodiode array. Various calibration problems were uncovered, such as those (1) due to system noise in recording the calibration tables, or (2) due to thermal drift and (3) due to the original quantization process. It was determined that in this experiment, noise and thermal drift led to fixed errors in the normalization of responses on the order of + or - 10 counts, out of 255 counts for many of the detectors.