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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

All sources NASA NTRS DOE OSTI

NASA NTRS1984

Measurement of thigmomorphogenesis and gravitropism by non-intrusive computerized video image processing

A video image processing instrument, DARWIN (Digital Analyser of Resolvable Whole-pictures by Image Numeration), was developed. It was programmed to measure stem or root growth and bending, and coupled to a specially mounted video camera to be able to automatically generate growth and bending curves during gravitropism. The growth of the plant is recorded on a video casette recorder with a specially modified time lapse function. At the end of the experiment, DARWIN analyses the growth or movement and prints out bending and growth curves. This system was used to measure thigmomorphagenesis in light grown corn plants. If the plant is rubbed with an applied force load of 0.38 N., it grows faster than the unrubbed control, whereas 1.14 N. retards its growth. Image analysis shows that most of the change in the rate of growth is caused in the first hour after rubbing. When DARWIN was used to measure gravitropism in dark grown oat seedlings, it was found that the top side of the shoot contracts during the first hour of gravitational stimulus, whereas the bottom side begins to elongate after 10 to 15 minutes.

Jaffe, M. J.↗

NASA NTRS1985

Video image processing

Current technology projections indicate a lack of availability of special purpose computing for Space Station applications. Potential functions for video image special purpose processing are being investigated, such as smoothing, enhancement, restoration and filtering, data compression, feature extraction, object detection and identification, pixel interpolation/extrapolation, spectral estimation and factorization, and vision synthesis. Also, architectural approaches are being identified and a conceptual design generated. Computationally simple algorithms will be research and their image/vision effectiveness determined. Suitable algorithms will be implimented into an overall architectural approach that will provide image/vision processing at video rates that are flexible, selectable, and programmable. Information is given in the form of charts, diagrams and outlines.

Murray, N. D.↗

NASA NTRS2016

Normalized Temperature Contrast Processing in Flash Infrared Thermography

The paper presents further development in normalized contrast processing of flash infrared thermography method by the author given in US 8,577,120 B1. The method of computing normalized image or pixel intensity contrast, and normalized temperature contrast are provided, including converting one from the other. Methods of assessing emissivity of the object, afterglow heat flux, reflection temperature change and temperature video imaging during flash thermography are provided. Temperature imaging and normalized temperature contrast imaging provide certain advantages over pixel intensity normalized contrast processing by reducing effect of reflected energy in images and measurements, providing better quantitative data. The subject matter for this paper mostly comes from US 9,066,028 B1 by the author. Examples of normalized image processing video images and normalized temperature processing video images are provided. Examples of surface temperature video images, surface temperature rise video images and simple contrast video images area also provided. Temperature video imaging in flash infrared thermography allows better comparison with flash thermography simulation using commercial software which provides temperature video as the output. Temperature imaging also allows easy comparison of surface temperature change to camera temperature sensitivity or noise equivalent temperature difference (NETD) to assess probability of detecting (POD) anomalies.

Koshti, Ajay M.↗

NASA NTRS1991

A 3-D nonlinear recursive digital filter for video image processing

This paper introduces a recursive 3-D nonlinear digital filter, which is capable of performing noise suppression without degrading important image information such as edges in space or time. It also has the property of unnoticeable bandwidth reduction immediately after a scene change, which makes the filter an attractive preprocessor to many interframe compression algorithms. The filter consists of a nonlinear 2-D spatial subfilter and a 1-D temporal filter. In order to achieve the required computational speed and increase the flexibility of the filter, all of the linear shift-variant filter modules are of the IIR type.

Bauer, P. H.↗

NASA NTRS2018

Two and Three Dimensional near Infrared Subcutaneous Structure Imager Using Real Time Nonlinear Video Processing

An imager is provided for viewing subcutaneous structures. In an embodiment of the invention, the imager includes a camera configured to generate a video frame, and an adaptive nonlinear processor. The adaptive nonlinear processor is configured to adjust a signal of the video frame below a first threshold to a maximum dark level and to adjust the signal of the video frame above a second threshold to a maximum light level. The imager further includes a display, configured to display the processed video frame.

Krasowski, Michael J↗

NASA NTRS2003

The VISAR Process

The Video Image Stabilization And Registration (VISAR) process is an award winning video image processing software developed at NASA's Marshall Space Flight Center. VISAR has a wide variety of application areas where the refinement of digital video is needed. It is used to correct jitter, rotation, and zoom effects by registering and processing on individual image captures that are a part of normal video capturing. Its most prominent uses were the 1996 Olympic Bombing case and in identifying Saddam Hussein during the Iraq war. Based on first-hand knowledge, this paper describes the VISAR process, which consists of several steps designed to refine digital video using VISAR software. The process determines the differences between two video images so that one, or both, of the images can be changed in ways that make them match as well as possible. Corrections include changes in position (horizontal and vertical image shifts), changes in orientation (image rotation), and changes in magnification (image zoom). While much of the VISAR process is automated, in its current embodiment it requires the user to initially identify the area of interest and to reset a threshold parameter if the default gives unacceptable results. The basic process that is used is an old tried and true method that determines how well the two images match. This process is called cross-correlation. It gives a single number, the correlation coefficient, that is equal to 1.0 if the images are perfectly matched, is equal to 0.0 if the images have nothing in common, and is equal to -1.0 if one image is the negative of the other. This basic process is used by many image stabilization methods. With VISAR we use it in a manner that provides statistical information needed to best determine orientation and magnification.

Hathaway, David↗

NASA NTRS1989

Gray-Scale Processing For Tracking Of Welds

Digital analysis of video-image-processing system contributes to automation of weld-seam tracking. Makes no contact with seam. Small television camera views seam just ahead of point currently being welded. Arc provides illumination. Periodically frame grabber digitizes video image and stores in computer memory as gray-scale values. Seam located by analyzing Hough-transform arrays of derivatives of digitally-filtered image data. Information on location and orientation of seam used as feedback by welding robot to correct deviations of electrode from seam as welding continues.

Gutow, David A.↗

NASA NTRS1990

Truncation Of Images For Correlation

Correlation performed on relatively small computer. Proposed method for processing video images in slowly changing scenes, renditions of complicated objects truncated to points, lines, polygons, or other simplified geometrical objects. Processed by image-correlating algorithms to extract information: recognize features and to track displacements of features in subsequent image frames to determine velocities. Entails correlation of far fewer data than original images.

Shimada, Katsunori↗

NASA NTRS1994

Video Event Trigger

Video event trigger (VET) processes video image data to generate trigger signal when image shows significant change like motion or appearance, disappearance, change in color, change in brightness, or dilation of object. System aids in efficient utilization of image-data-storage and image-data-processing equipment in applications in which many video frames show no changes and are wasteful to record and analyze all frames when only relatively few frames show changes of interest. Applications include video recording of automobile crash tests, automated video monitoring of entrances, exits, parking lots, and secure areas.

Williams, Glenn L.↗

NASA NTRS2008

Remote-Sensing Time Series Analysis, a Vegetation Monitoring Tool

The Time Series Product Tool (TSPT) is software, developed in MATLAB , which creates and displays high signal-to- noise Vegetation Indices imagery and other higher-level products derived from remotely sensed data. This tool enables automated, rapid, large-scale regional surveillance of crops, forests, and other vegetation. TSPT temporally processes high-revisit-rate satellite imagery produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) and by other remote-sensing systems. Although MODIS imagery is acquired daily, cloudiness and other sources of noise can greatly reduce the effective temporal resolution. To improve cloud statistics, the TSPT combines MODIS data from multiple satellites (Aqua and Terra). The TSPT produces MODIS products as single time-frame and multitemporal change images, as time-series plots at a selected location, or as temporally processed image videos. Using the TSPT program, MODIS metadata is used to remove and/or correct bad and suspect data. Bad pixel removal, multiple satellite data fusion, and temporal processing techniques create high-quality plots and animated image video sequences that depict changes in vegetation greenness. This tool provides several temporal processing options not found in other comparable imaging software tools. Because the framework to generate and use other algorithms is established, small modifications to this tool will enable the use of a large range of remotely sensed data types. An effective remote-sensing crop monitoring system must be able to detect subtle changes in plant health in the earliest stages, before the effects of a disease outbreak or other adverse environmental conditions can become widespread and devastating. The integration of the time series analysis tool with ground-based information, soil types, crop types, meteorological data, and crop growth models in a Geographic Information System, could provide the foundation for a large-area crop-surveillance system that could identify a variety of plant phenomena and improve monitoring capabilities.

McKellip, Rodney↗

NASA NTRS2008

Immersive Photography Renders 360 degree Views

An SBIR contract through Langley Research Center helped Interactive Pictures Corporation, of Knoxville, Tennessee, create an innovative imaging technology. This technology is a video imaging process that allows real-time control of live video data and can provide users with interactive, panoramic 360 views. The camera system can see in multiple directions, provide up to four simultaneous views, each with its own tilt, rotation, and magnification, yet it has no moving parts, is noiseless, and can respond faster than the human eye. In addition, it eliminates the distortion caused by a fisheye lens, and provides a clear, flat view of each perspective.

Source record↗

NASA NTRS2006

Remote Sensing Time Series Product Tool

The TSPT (Time Series Product Tool) software was custom-designed for NASA to rapidly create and display single-band and band-combination time series, such as NDVI (Normalized Difference Vegetation Index) images, for wide-area crop surveillance and for other time-critical applications. The TSPT, developed in MATLAB, allows users to create and display various MODIS (Moderate Resolution Imaging Spectroradiometer) or simulated VIIRS (Visible/Infrared Imager Radiometer Suite) products as single images, as time series plots at a selected location, or as temporally processed image videos. Manually creating these types of products is extremely labor intensive; however, the TSPT development tool makes the process simplified and efficient. MODIS is ideal for monitoring large crop areas because of its wide swath (2330 km), its relatively small ground sample distance (250 m), and its high temporal revisit time (twice daily). Furthermore, because MODIS imagery is acquired daily, rapid changes in vegetative health can potentially be detected. The new TSPT technology provides users with the ability to temporally process high-revisit-rate satellite imagery, such as that acquired from MODIS and from its successor, the VIIRS. The TSPT features the important capability of fusing data from both MODIS instruments onboard the Terra and Aqua satellites, which drastically improves cloud statistics. With the TSPT, MODIS metadata is used to find and optionally remove bad and suspect data. Noise removal and temporal processing techniques allow users to create low-noise time series plots and image videos and to select settings and thresholds that tailor particular output products. The TSPT GUI (graphical user interface) provides an interactive environment for crafting what-if scenarios by enabling a user to repeat product generation using different settings and thresholds. The TSPT Application Programming Interface provides more fine-tuned control of product generation, allowing experienced programmers to bypass the GUI and to create more user-specific output products, such as comparison time plots or images. This type of time series analysis tool for remotely sensed imagery could be the basis of a large-area vegetation surveillance system. The TSPT has been used to generate NDVI time series over growing seasons in California and Argentina and for hurricane events, such as Hurricane Katrina.

Predos, Don↗

NASA NTRS1994

SSME propellant path leak detection real-time

Included are four documents that outline the technical aspects of the research performed on NASA Grant NAG8-140: 'A System for Sequential Step Detection with Application to Video Image Processing'; 'Leak Detection from the SSME Using Sequential Image Processing'; 'Digital Image Processor Specifications for Real-Time SSME Leak Detection'; and 'A Color Change Detection System for Video Signals with Applications to Spectral Analysis of Rocket Engine Plumes'.

Crawford, R. A.↗

NASA NTRS1971

Feasibility study for automatic reduction of phase change imagery

The feasibility of automatically reducing a form of pictorial aerodynamic heating data is discussed. The imagery, depicting the melting history of a thin coat of fusible temperature indicator painted on an aerodynamically heated model, was previously reduced by manual methods. Careful examination of various lighting theories and approaches led to an experimentally verified illumination concept capable of yielding high-quality imagery. Both digital and video image processing techniques were applied to reduction of the data, and it was demonstrated that either method can be used to develop superimposed contours. Mathematical techniques were developed to find the model-to-image and the inverse image-to-model transformation using six conjugate points, and methods were developed using these transformations to determine heating rates on the model surface. A video system was designed which is able to reduce the imagery rapidly, economically and accurately. Costs for this system were estimated. A study plan was outlined whereby the mathematical transformation techniques developed to produce model coordinate heating data could be applied to operational software, and methods were discussed and costs estimated for obtaining the digital information necessary for this software.

Nossaman, G. O.↗

NASA NTRS1972

Bonanza project, 1971

Research on the application of remote sensing techniques to the mineral industry stresses photointerpretation by human interpreter experienced in the extraction of geological information from aerial color and multiband photographs and from thermal scanner imagery. Also considered are optical and digital image enhancement, multiband color additive projection, video image processing, and computer reduction and analysis of infrared spectrometry. Evaluation of those parameters which have the most contrast between adjacent rock formations and which can be remotely sensed establish the following most useful geological characteristics: Topographic landform, color, albedo, and surface temperature.

Lee, K.↗

NASA NTRS1980

Image-based information, communication, and retrieval

IBIS/VICAR system combines video image processing and information management. Flexible programs require user to supply only parameters specific to particular application. Special-purpose input/output routines transfer image data with reduced memory requirements. New application programs are easily incorporated. Program is written in FORTRAN IV, Assembler, and OS JCL for batch execution and has been implemented on IBM 360.

Bryant, N. A.↗

NASA NTRS1988

Plant health sensing

If plants are to be used as a food source for long term space missions, they must be grown in a stable environment where the health of the crops is continuously monitored. The sensor(s) to be used should detect any diseases or health problems before irreversible damage occurs. The method of analysis must be nondestructive and provide instantaneous information on the condition of the crop. In addition, the sensor(s) must be able to function in microgravity. This first semester, the plant health and disease sensing group concentrated on researching and consulting experts in many fields in attempts to find reliable plant health indicators. Once several indicators were found, technologies that could detect them were investigated. Eventually the three methods chosen to be implemented next semester were stimulus response monitoring, video image processing and chlorophyll level detection. Most of the other technologies investigated this semester are discussed here. They were rejected for various reasons but are included in the report because NASA may wish to consider pursuing them in the future.

Manukian, Ara↗

NASA NTRS1989

CCD TV focal plane guider development and comparison to SIRTF applications

It is expected that the SIRTF payload will use a CCD TV focal plane fine guidance sensor to provide acquisition of sources and tracking stability of the telescope. Work has been done to develop CCD TV cameras and guiders at Lick Observatory for several years and have produced state of the art CCD TV systems for internal use. NASA decided to provide additional support so that the limits of this technology could be established and a comparison between SIRTF requirements and practical systems could be put on a more quantitative basis. The results of work carried out at Lick Observatory which was designed to characterize present CCD autoguiding technology and relate it to SIRTF applications is presented. Two different design types of CCD cameras were constructed using virtual phase and burred channel CCD sensors. A simple autoguider was built and used on the KAO, Mt. Lemon and Mt. Hamilton telescopes. A video image processing system was also constructed in order to characterize the performance of the auto guider and CCD cameras.

Rank, David M.↗