Search NASA⌕ Search

SEARCH · Search NASA

Results for “image detection”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Direct and interferometric imaging approaches for detecting earth-like extrasolar planets

This paper discusses functional requirements of space-based observational systems with sufficient sensitivity, resolution, and dynamic range to image earth-like extrasolar planets within a search radius of 10 parsecs from the sun. Both direct and interferometric systems operating at visible and infrared wavelengths are evaluated, and the methods used to establish the system tolerances are presented. Due to the more favorable star/planet contrast ratio in the infrared, optical tolerance requirements are less stringent than in the visible. However, reduction of thermal radiation from the telescope requires cooling of the primary optics. Other tradeoffs between various approaches are enumerated.

Diner, D. J.↗
NASA NTRS1994

Synthetic aperture radar target detection, feature extraction, and image formation techniques

This report presents new algorithms for target detection, feature extraction, and image formation with the synthetic aperture radar (SAR) technology. For target detection, we consider target detection with SAR and coherent subtraction. We also study how the image false alarm rates are related to the target template false alarm rates when target templates are used for target detection. For feature extraction from SAR images, we present a computationally efficient eigenstructure-based 2D-MODE algorithm for two-dimensional frequency estimation. For SAR image formation, we present a robust parametric data model for estimating high resolution range signatures of radar targets and for forming high resolution SAR images.

Li, Jian↗
NASA NTRS1993

Cirrus cloud detection from airborne imaging spectrometer data using the 1.38 micron water vapor band

Using special images acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) at 20 km altitude, we show that wavelengths close to the center of the strong 1.38 micron water vapor band are useful for detecting thin cirrus clouds. The detection makes use of the fact that cirrus clouds are located above almost all the atmospheric water vapor. Because of the strong water vapor absorption in the lower atmosphere, AVIRIS channels near 1.38 micron receive little scattered solar radiance from the surface of low level clouds. When cirrus clouds are present, however, these channels receive large amounts of scattered solar radiance from the cirrus clouds. Our ability to determine cirrus cloud cover using space-based remote sensing will be improved if channels near the center of the 1.38 micron water vapor band are added to future satellites.

Gao, Bo-Cai↗
NASA NTRS1997

Detection of Obstacles in Monocular Image Sequences

The ability to detect and locate runways/taxiways and obstacles in images captured using on-board sensors is an essential first step in the automation of low-altitude flight, landing, takeoff, and taxiing phase of aircraft navigation. Automation of these functions under different weather and lighting situations, can be facilitated by using sensors of different modalities. An aircraft-based Synthetic Vision System (SVS), with sensors of different modalities mounted on-board, complements the current ground-based systems in functions such as detection and prevention of potential runway collisions, airport surface navigation, and landing and takeoff in all weather conditions. In this report, we address the problem of detection of objects in monocular image sequences obtained from two types of sensors, a Passive Millimeter Wave (PMMW) sensor and a video camera mounted on-board a landing aircraft. Since the sensors differ in their spatial resolution, and the quality of the images obtained using these sensors is not the same, different approaches are used for detecting obstacles depending on the sensor type. These approaches are described separately in two parts of this report. The goal of the first part of the report is to develop a method for detecting runways/taxiways and objects on the runway in a sequence of images obtained from a moving PMMW sensor. Since the sensor resolution is low and the image quality is very poor, we propose a model-based approach for detecting runways/taxiways. We use the approximate runway model and the position information of the camera provided by the Global Positioning System (GPS) to define regions of interest in the image plane to search for the image features corresponding to the runway markers. Once the runway region is identified, we use histogram-based thresholding to detect obstacles on the runway and regions outside the runway. This algorithm is tested using image sequences simulated from a single real PMMW image.

Kasturi, Rangachar↗
NASA NTRS2001

Utilization of an Airborne Plant Chlorophyll Imaging System for Detection of Septic System Malfunction

Malfunctioning, or leaking, sewer systems increase the supply of water and nutrients to surface vegetation. Excess nutrients and harmful bacteria in the effluent pollute ground water and local water bodies and are dangerous to humans and the aquatic ecosystems. An airborne multispectral plant chlorophyll imaging system (PCIS) was used to identify growth patterns in the vegetation covering onsite and public sewer systems. The objective was to evaluate overall performance of the PCIS as well as to determine the best operational configuration for this application. The imaging system was flown in a light aircraft over selected locations Mobile County, Alabama. Calibration panels were used to help characterize instrument performance. Results demonstrated that the PCIS performed well and was capable of detecting septic leakage patterns from altitudes as high as 915 m. From 915 m, 6 of 18 sites were suspected to have sewage leakage. Subsequent ground inspections confirmed leakage on 3 of the 6 sites. From 610 m, 3 of 8 known leakage sites were detected. Tree cover and shadows near residential structures prevented detection of several known malfunctioning systems. Also some leakages known to occur in clear areas were not detected. False detections occurred in areas characterized by surface water drainage problems or recent excavation.

Spiering, Bruce A.↗
NASA NTRS2010

Ice Sheet Change Detection by Satellite Image Differencing

Differencing of digital satellite image pairs highlights subtle changes in near-identical scenes of Earth surfaces. Using the mathematical relationships relevant to photoclinometry, we examine the effectiveness of this method for the study of localized ice sheet surface topography changes using numerical experiments. We then test these results by differencing images of several regions in West Antarctica, including some where changes have previously been identified in altimeter profiles. The technique works well with coregistered images having low noise, high radiometric sensitivity, and near-identical solar illumination geometry. Clouds and frosts detract from resolving surface features. The ETM(plus) sensor on Landsat-7, ALI sensor on EO-1, and MODIS sensor on the Aqua and Terra satellite platforms all have potential for detecting localized topographic changes such as shifting dunes, surface inflation and deflation features associated with sub-glacial lake fill-drain events, or grounding line changes. Availability and frequency of MODIS images favor this sensor for wide application, and using it, we demonstrate both qualitative identification of changes in topography and quantitative mapping of slope and elevation changes.

Bindschadler, Robert A.↗
NASA NTRS2016

Lenslet Array to Further Suppress Star Light for Direct Exoplanet Detection

Direct imaging plays a key role in the detection and characterization of exoplanets orbiting within its host star's habitable zone. Many innovative ideas for starlight suppression and wavefront control have been proposed and developed over the past decade. However, several technological challenges still lie ahead to achieve the required contrast, including controlling the observatory pointing performance, fabricating occulting masks with tight optical tolerances, developing wavefront control algorithms, controlling stray light, advancing single photon detecting detectors, and integrated system-level issues. This paper explores how a lenslet array and pinhole mask may be implemented to further suppress uncorrected starlight that leaks through the occulting mask. An external occulter, or star shade, is simulated to demonstrate this concept, although this approach can be implemented for internal coronagraphs as well. We describe how to use simple relay optics to control the scene near the inner working angle and the level of the suppression expected. Furthermore, if the lenslet array is the input to an integral field spectrograph, as planned for the WFIRST mission, the spectral content of the exoplanet atmospheres can be obtained to determine if the observed planet is habitable and ultimately, if it is inhabited.

Integral Field spectrograph↗
NASA NTRS1989

IBIS: An Interferometer-Based Imaging System for Detecting Extrasolar Planets with a Next Generation Space Telescope

The direct detection of extrasolar planetary systems is a challenging observational objective. The observing system must be able to detect faint planetary signals against the background of diffracted and scattered starlight, zodiacal light, and in the IR, mirror thermal radiation. As part of a JPL study, we concluded that the best long-term approach is a 10-20 m filled-aperture telescope operating in the thermal IR (10-15 microns). At these wavelengths, the star/planet flux ratio is on the order of 10(exp 6)-10(exp 8). Our study supports the work of Angel et al., who proposed a cooled 16-m IR telescope and a special apodization mask to suppress the stellar light within a limited angular region around the star. Our scheme differs in that it is capable of stellar suppression over a much broader field-of- view, enabling more efficient planet searches. To do this, certain key optical signal-processing components are needed, including a coronagraph to apodize the stellar diffraction pattern, an infrared interferometer to provide further starlight suppression, a complementary visible-wavelength interferometer to sense figure errors in the telescope optics, and a deformable mirror to adaptively compensate for these errors. Because of the central role of interferometry we have designated this concept the Interferometer-Based Imaging System (IBIS). IBIS incorporates techniques originally suggested by Ken Knight for extrasolar planet detection at visible wavelengths. The type of telescope discussed at this workshop is well suited to implementation of the IBIS concept.

Diner, David J.↗
NASA NTRS1995

Trainable Cataloging for Digital Image Libraries with Applications to Volcano Detection

Users of digital image libraries are often not interested in image data per se but in derived products such as catalogs of objects of interest. Converting an image database into a usable catalog is typically carried out manually at present. For many larger image databases the purely manual approach is completely impractical. In this paper we describe the development of a trainable cataloging system: the user indicates the location of the objects of interest for a number of training images and the system learns to detect and catalog these objects in the rest of the database. In particular we describe the application of this system to the cataloging of small volcanoes in radar images of Venus. The volcano problem is of interest because of the scale (30,000 images, order of 1 million detectable volcanoes), technical difficulty (the variability of the volcanoes in appearance) and the scientific importance of the problem. The problem of uncertain or subjective ground truth is of fundamental importance in cataloging problems of this nature and is discussed in some detail. Experimental results are presented which quantify and compare the detection performance of the system relative to human detection performance. The paper concludes by discussing the limitations of the proposed system and the lessons learned of general relevance to the development of digital image libraries.

digital image libraries, trainable cataloging↗
NASA NTRS2010

Landmark Detection in Orbital Images Using Salience Histograms

NASA's planetary missions have collected, and continue to collect, massive volumes of orbital imagery. The volume is such that it is difficult to manually review all of the data and determine its significance. As a result, images are indexed and searchable by location and date but generally not by their content. A new automated method analyzes images and identifies "landmarks," or visually salient features such as gullies, craters, dust devil tracks, and the like. This technique uses a statistical measure of salience derived from information theory, so it is not associated with any specific landmark type. It identifies regions that are unusual or that stand out from their surroundings, so the resulting landmarks are context-sensitive areas that can be used to recognize the same area when it is encountered again. A machine learning classifier is used to identify the type of each discovered landmark. Using a specified window size, an intensity histogram is computed for each such window within the larger image (sliding the window across the image). Next, a salience map is computed that specifies, for each pixel, the salience of the window centered at that pixel. The salience map is thresholded to identify landmark contours (polygons) using the upper quartile of salience values. Descriptive attributes are extracted for each landmark polygon: size, perimeter, mean intensity, standard deviation of intensity, and shape features derived from an ellipse fit.

Wagstaff, Kiri L.↗
NASA NTRS2011

Superpixel-Augmented Endmember Detection for Hyperspectral Images

Superpixels are homogeneous image regions comprised of several contiguous pixels. They are produced by shattering the image into contiguous, homogeneous regions that each cover between 20 and 100 image pixels. The segmentation aims for a many-to-one mapping from superpixels to image features; each image feature could contain several superpixels, but each superpixel occupies no more than one image feature. This conservative segmentation is relatively easy to automate in a robust fashion. Superpixel processing is related to the more general idea of improving hyperspectral analysis through spatial constraints, which can recognize subtle features at or below the level of noise by exploiting the fact that their spectral signatures are found in neighboring pixels. Recent work has explored spatial constraints for endmember extraction, showing significant advantages over techniques that ignore pixels relative positions. Methods such as AMEE (automated morphological endmember extraction) express spatial influence using fixed isometric relationships a local square window or Euclidean distance in pixel coordinates. In other words, two pixels covariances are based on their spatial proximity, but are independent of their absolute location in the scene. These isometric spatial constraints are most appropriate when spectral variation is smooth and constant over the image. Superpixels are simple to implement, efficient to compute, and are empirically effective. They can be used as a preprocessing step with any desired endmember extraction technique. Superpixels also have a solid theoretical basis in the hyperspectral linear mixing model, making them a principled approach for improving endmember extraction. Unlike existing approaches, superpixels can accommodate non-isometric covariance between image pixels (characteristic of discrete image features separated by step discontinuities). These kinds of image features are common in natural scenes. Analysts can substitute superpixels for image pixels during endmember analysis that leverages the spatial contiguity of scene features to enhance subtle spectral features. Superpixels define populations of image pixels that are independent samples from each image feature, permitting robust estimation of spectral properties, and reducing measurement noise in proportion to the area of the superpixel. This permits improved endmember extraction, and enables automated search for novel and constituent minerals in very noisy, hyperspatial images. This innovation begins with a graph-based segmentation based on the work of Felzenszwalb et al., but then expands their approach to the hyperspectral image domain with a Euclidean distance metric. Then, the mean spectrum of each segment is computed, and the resulting data cloud is used as input into sequential maximum angle convex cone (SMACC) endmember extraction.

Thompson, David R.↗
NASA NTRS2011

Wavenumber Imaging For Damage Detection and Measurement

This paper presents a method for analyzing ultrasonic wavefield data using the Continuous Wavelet Transform (CWT) applied in the spatial domain. Unlike data obtained by sparse arrays of transducers, full wavefield data contains information local to the structure and can be used to obtain more detailed measurements of damage type, location, size, etc. By calculating the CWT of the wavefield in the spatial domain, the wavenumber spectrum is determined for the inspected locations. Because wavenumber is affected by the local geometry and material properties of the structure through which Lamb waves propagate, the wavenumber spectrum can be analyzed to assess the location, severity, and size of damage. The technique is first applied to experimental wavefield data obtained using a laser Doppler vibrometer and automated positioning stage. The out-of-plane velocity along the length of a composite stringer was measured to detect the presence of delaminations within the composite overwrap. Next, simulated corrosion is detected and measured within an aluminum plate using the two dimensional CWT. The experimental results show the usefulness of the technique for vehicle structure inspection applications.

Rogge, Matthew D.↗
NASA NTRS2012

Low field electron paramagnetic resonance imaging with SQUID detection

In one embodiment, a flux transformer with a gradiometer pickup coil is magnetically coupled to a SQUID, and a SQUID array amplifier comprising a plurality of SQUIDs, connected in series, is magnetically coupled to the output of the SQUID. Other embodiments are described and claimed.

Hahn, Inseob↗