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At least 703 records · Page 39

Optical Processing of Speckle Images with Bacteriorhodopsin for Pattern Recognition

Logarithmic processing of images with multiplicative noise characteristics can be utilized to transform the image into one with an additive noise distribution. This simplifies subsequent image processing steps for applications such as image restoration or correlation for pattern recognition. One particularly common form of multiplicative noise is speckle, for which the logarithmic operation not only produces additive noise, but also makes it of constant variance (signal-independent). We examine the optical transmission properties of some bacteriorhodopsin films here and find them well suited to implement such a pointwise logarithmic transformation optically in a parallel fashion. We present experimental results of the optical conversion of speckle images into transformed images with additive, signal-independent noise statistics using the real-time photochromic properties of bacteriorhodopsin. We provide an example of improved correlation performance in terms of correlation peak signal-to-noise for such a transformed speckle image.

Downie, John D.↗

Hyperspectral Imaging and Spectroscopy of Fluorescently Coupled Acyl-CoA: Cholesterol Acyltransferase in Insect Cells

A high-performance hyperspectral imaging module with high throughput of light suitable for low-intensity fluorescence microscopic imaging and subsequent analysis, including single-pixel-defined emission spectroscopy, was tested on Sf21 insect cells expressing green fluorescence associated with recombinant green fluorescent protein linked or not with the membrane protein acyl-CoA:cholesterol acyltransferase. The imager utilized the phenomenon of optical activity as a new technique providing information over a spectral range of 220-1400 nm, and was inserted between the microscope and an 8-bit CCD video-rate camera. The resulting fluorescence image did not introduce observable image aberrations. The images provided parallel acquisition of well resolved concurrent spatial and spectral information such that fluorescence associated with green fluorescent protein alone was demonstrated to be diffuse within the Sf21 insect cell, and that green fluorescence associated with the membrane protein was shown to be specifically concentrated within regions of the cell cytoplasm. Emission spectra analyzed from different regions of the fluorescence image showed blue shift specific for the regions of concentration associated with the membrane protein.

Malak, H.↗

Electron Microscopy and Image Analysis for Selected Materials

This particular project was completed in collaboration with the metallurgical diagnostics facility. The objective of this research had four major components. First, we required training in the operation of the environmental scanning electron microscope (ESEM) for imaging of selected materials including biological specimens. The types of materials range from cyanobacteria and diatoms to cloth, metals, sand, composites and other materials. Second, to obtain training in surface elemental analysis technology using energy dispersive x-ray (EDX) analysis, and in the preparation of x-ray maps of these same materials. Third, to provide training for the staff of the metallurgical diagnostics and failure analysis team in the area of image processing and image analysis technology using NIH Image software. Finally, we were to assist in the sample preparation, observing, imaging, and elemental analysis for Mr. Richard Hoover, one of NASA MSFC's solar physicists and Marshall's principal scientist for the agency-wide virtual Astrobiology Institute. These materials have been collected from various places around the world including the Fox Tunnel in Alaska, Siberia, Antarctica, ice core samples from near Lake Vostoc, thermal vents in the ocean floor, hot springs and many others. We were successful in our efforts to obtain high quality, high resolution images of various materials including selected biological ones. Surface analyses (EDX) and x-ray maps were easily prepared with this technology. We also discovered and used some applications for NIH Image software in the metallurgical diagnostics facility.

Williams, George↗

Hyperspectral Image Classification using a Self-Organizing Map

The use of hyperspectral data to determine the abundance of constituents in a certain portion of the Earth's surface relies on the capability of imaging spectrometers to provide a large amount of information at each pixel of a certain scene. Today, hyperspectral imaging sensors are capable of generating unprecedented volumes of radiometric data. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), for example, routinely produces image cubes with 224 spectral bands. This undoubtedly opens a wide range of new possibilities, but the analysis of such a massive amount of information is not an easy task. In fact, most of the existing algorithms devoted to analyzing multispectral images are not applicable in the hyperspectral domain, because of the size and high dimensionality of the images. The application of neural networks to perform unsupervised classification of hyperspectral data has been tested by several authors and also by us in some previous work. We have also focused on analyzing the intrinsic capability of neural networks to parallelize the whole hyperspectral unmixing process. The results shown in this work indicate that neural network models are able to find clusters of closely related hyperspectral signatures, and thus can be used as a powerful tool to achieve the desired classification. The present work discusses the possibility of using a Self Organizing neural network to perform unsupervised classification of hyperspectral images. In sections 3 and 4, the topology of the proposed neural network and the training algorithm are respectively described. Section 5 provides the results we have obtained after applying the proposed methodology to real hyperspectral data, described in section 2. Different parameters in the learning stage have been modified in order to obtain a detailed description of their influence on the final results. Finally, in section 6 we provide the conclusions at which we have arrived.

Martinez, P.↗

Industrial X-Ray Imaging

In 1990, Lewis Research Center jointly sponsored a conference with the U.S. Air Force Wright Laboratory focused on high speed imaging. This conference, and early funding by Lewis Research Center, helped to spur work by Silicon Mountain Design, Inc. to break the performance barriers of imaging speed, resolution, and sensitivity through innovative technology. Later, under a Small Business Innovation Research contract with the Jet Propulsion Laboratory, the company designed a real-time image enhancing camera that yields superb, high quality images in 1/30th of a second while limiting distortion. The result is a rapidly available, enhanced image showing significantly greater detail compared to image processing executed on digital computers. Current applications include radiographic and pathology-based medicine, industrial imaging, x-ray inspection devices, and automated semiconductor inspection equipment.

Source record↗

Evaluation of a ''CMOS'' Imager for Shadow Mask Hard X-ray Telescope

We have developed a hard x-ray coder that provides high angular resolution imaging capability using a coarse position sensitive image plane detector. The coder consists of two Fresnel zone plates. (FZP) Two such 'FZP's generate Moire fringe patterns whose frequency and orientation define the arrival direction of a beam with respect to telescope axis. The image plane detector needs to resolve the Moire fringe pattern. Pixilated detectors can be used as an image plane detector. The recently available 'CMOS' imager could provide a very low power large area image plane detector for hard x-rays. We have looked into a unit made by Rad-Icon Imaging Corp. The Shadow-Box 1024 x-ray camera is a high resolution 1024xl024 pixel detector of 50x50 mm area. It is a very low power, stand alone camera. We present some preliminary results of our investigation of evaluation of such camera.

Desai, Upendra D.↗

Hot Views on Cold Crystals: The Application of Thermal Imaging in Cryocrystallography

We have used thermal imaging techniques to visualize the cryocooling processes of macromolecular crystals. Cryocooling is a common technique used for structural data collection to reduce radiation damage in intense X-ray beams and decrease the thermal motion of the atoms. From the thermal images it was clear that during cryocooling a cold wave progresses through a crystal starting at the face closest to the origin of the cold stream and ending at the point furthest away. As an extension to this work, we used thermal imaging to study small crystals, held in a cryo-loop, in the presence of vitrified mother liquor. The different infrared transmission and reflectance properties of the crystal in comparison to the mother liquor surrounding it are thought to be the parameter that produces the contrast that makes the crystal visible. An application of this technology may be the determination of the exact location of small crystals in a cryo-loop for automated structural genomics studies. Data from initial tests in support of application development was recorded for lysozyme crystals and for bFGF/dna complex crystals, which were cryocooled and imaged in large loops, both with visible light and with infrared radiation. The crystals were clearly distinguished from the vitrified solution in the infrared spectrum, while in the case of the bFGF/dna complex the illumination had to be carefully manipulated to make the crystal visible in the visible spectrum. These results suggest that the thermal imaging may be more sensitive than visual imaging for automated location of small crystals. However, further work on small crystals robotically mounted at SSRL did not clearly visualize those crystals. The depth of field of the camera proved to be limiting and a different cooling geometry was used, compared to the previous, successful experiments. Analysis to exploit multiple images to improve depth of field and experimental work to understand cooling geometry effects is ongoing. These results will be presented along with advantages and disadvantages of the technique and a discussion of how it might be applied.

Snell, Eddie↗

Software for Viewing Landsat Mosaic Images

A Windows-based computer program has been written to enable novice users (especially educators and students) to view images of large areas of the Earth (e.g., the continental United States) generated from image data acquired in the Landsat observations performed circa the year 1990. The large-area images are constructed as mosaics from the original Landsat images, which were acquired in several wavelength bands and each of which spans an area (in effect, one tile of a mosaic) of approx. 5 in latitude by approx. 6 deg in longitude. Whereas the original Landsat data are registered on a universal transverse Mercator (UTM) grid, the program converts the UTM coordinates of a mouse pointer in the image to latitude and longitude, which are continuously updated and displayed as the pointer is moved. The mosaic image currently on display can be exported as a Windows bit-map file. Other images (e.g., of state boundaries or interstate highways) can be overlaid on Landsat mosaics. The program interacts with the user via standard toolbar, keyboard, and mouse user interfaces. The program is supplied on a compact disk along with tutorial and educational information.

Source record↗

Hierarchical Image Segmentation of Remotely Sensed Data using Massively Parallel GNU-LINUX Software

A hierarchical set of image segmentations is a set of several image segmentations of the same image at different levels of detail in which the segmentations at coarser levels of detail can be produced from simple merges of regions at finer levels of detail. In [1], Tilton, et a1 describes an approach for producing hierarchical segmentations (called HSEG) and gave a progress report on exploiting these hierarchical segmentations for image information mining. The HSEG algorithm is a hybrid of region growing and constrained spectral clustering that produces a hierarchical set of image segmentations based on detected convergence points. In the main, HSEG employs the hierarchical stepwise optimization (HSWO) approach to region growing, which was described as early as 1989 by Beaulieu and Goldberg. The HSWO approach seeks to produce segmentations that are more optimized than those produced by more classic approaches to region growing (e.g. Horowitz and T. Pavlidis, [3]). In addition, HSEG optionally interjects between HSWO region growing iterations, merges between spatially non-adjacent regions (i.e., spectrally based merging or clustering) constrained by a threshold derived from the previous HSWO region growing iteration. While the addition of constrained spectral clustering improves the utility of the segmentation results, especially for larger images, it also significantly increases HSEG s computational requirements. To counteract this, a computationally efficient recursive, divide-and-conquer, implementation of HSEG (RHSEG) was devised, which includes special code to avoid processing artifacts caused by RHSEG s recursive subdivision of the image data. The recursive nature of RHSEG makes for a straightforward parallel implementation. This paper describes the HSEG algorithm, its recursive formulation (referred to as RHSEG), and the implementation of RHSEG using massively parallel GNU-LINUX software. Results with Landsat TM data are included comparing RHSEG with classic region growing.

Tilton, James C.↗

Software for Viewing Landsat Mosaic Images

A Windows-based computer program has been written to enable novice users (especially educators and students) to view images of large areas of the Earth (e.g., the continental United States) generated from image data acquired in the Landsat observations performed circa the year 1990. The large-area images are constructed as mosaics from the original Landsat images, which were acquired in several wavelength bands and each of which spans an area (in effect, one tile of a mosaic) of 5 in latitude by approximately equal to 6 degrees in longitude. Whereas the original Landsat data are registered on a universal transverse Mercator (UTM) grid, the program converts the UTM coordinates of a mouse pointer in the image to latitude and longitude, which are continuously updated and displayed as the pointer is moved. The mosaic image currently on display can be exported as a Windows bit-map file. Other images (e.g., of state boundaries or interstate highways) can be overlaid on Landsat mosaics. The program interacts with the user via standard toolbar, keyboard, and mouse user interfaces. The program is supplied on a compact disk along with tutorial and educational information.

Watts, Jack↗

Accuracy for detection of simulated lesions: comparison of fluid-attenuated inversion-recovery, proton density--weighted, and T2-weighted synthetic brain MR imaging

OBJECTIVE: The objective of our study was to determine the effects of MR sequence (fluid-attenuated inversion-recovery [FLAIR], proton density--weighted, and T2-weighted) and of lesion location on sensitivity and specificity of lesion detection. MATERIALS AND METHODS: We generated FLAIR, proton density-weighted, and T2-weighted brain images with 3-mm lesions using published parameters for acute multiple sclerosis plaques. Each image contained from zero to five lesions that were distributed among cortical-subcortical, periventricular, and deep white matter regions; on either side; and anterior or posterior in position. We presented images of 540 lesions, distributed among 2592 image regions, to six neuroradiologists. We constructed a contingency table for image regions with lesions and another for image regions without lesions (normal). Each table included the following: the reviewer's number (1--6); the MR sequence; the side, position, and region of the lesion; and the reviewer's response (lesion present or absent [normal]). We performed chi-square and log-linear analyses. RESULTS: The FLAIR sequence yielded the highest true-positive rates (p < 0.001) and the highest true-negative rates (p < 0.001). Regions also differed in reviewers' true-positive rates (p < 0.001) and true-negative rates (p = 0.002). The true-positive rate model generated by log-linear analysis contained an additional sequence-location interaction. The true-negative rate model generated by log-linear analysis confirmed these associations, but no higher order interactions were added. CONCLUSION: We developed software with which we can generate brain images of a wide range of pulse sequences and that allows us to specify the location, size, shape, and intrinsic characteristics of simulated lesions. We found that the use of FLAIR sequences increases detection accuracy for cortical-subcortical and periventricular lesions over that associated with proton density- and T2-weighted sequences.

NASA Discipline Neuroscience↗

Automated Recognition of Geologically Significant Shapes in MER PANCAM and MI Images

Autonomous recognition of scientifically important information provides the capability of: 1) Prioritizing data return; 2) Intelligent data compression; 3) Reactive behavior onboard robotic vehicles. Such capabilities are desirable as mission scenarios include longer durations with decreasing interaction from mission control. To address such issues, we have implemented several computer algorithms, intended to autonomously recognize morphological shapes of scientific interest within a software architecture envisioned for future rover missions. Mars Exploration Rovers (MER) instrument payloads include a Panoramic Camera (PANCAM) and Microscopic Imager (MI). These provide a unique opportunity to evaluate our algorithms when applied to data obtained from the surface of Mars. Early in the mission we applied our algorithms to images available at the mission web site (http://marsrovers.jpl.nasa.gov/gallery/images.html), even though these are not at full resolution. Some algorithms would normally use ancillary information, e.g. camera pointing and position of the sun, but these data were not readily available. The initial results of applying our algorithms to the PANCAM and MI images are encouraging. The horizon is recognized in all images containing it; such information could be used to eliminate unwanted areas from the image prior to data transmission to Earth. Additionally, several rocks were identified that represent targets for the mini-thermal emission spectrometer. Our algorithms also recognize the layers, identified by mission scientists. Such information could be used to prioritize data return or in a decision-making process regarding future rover activities. The spherules seen in MI images were also autonomously recognized. Our results indicate that reliable recognition of scientifically relevant morphologies in images is feasible.

Morris, Robert↗

The Utility of Auroral Image-based Activities Metrics

Auroral activity indices such as Hemispheric Power and Auroral Boundary are currently key data products used for space weather predictions and nowcasting. However, these products are necessarily based on limited observations which must be extrapolated to provide global coverage. The advent of routine space-based auroral imaging in the last decade offers the seeming advantage of more detailed measures of auroral activity. Examples of image-derived products include energy deposition maps, oval location, cap size, and morphological classification. However, activity metrics derived from auroral images have shortcomings, as well. For example, limited fields-of-view and orbital motion prevent full coverage of the auroral regions. This paper will examine the utility of activity metrics derived h m auroral images for operational purposes. The eight-year collection of Polar UVI images databased in the UVI Online Search Tool (OST) will be used to illustrate the advantages and shortcomings of auroral activity metrics. The potential role of other currently-active imaging missions will also be examined and correlative studies to date using auroral imaging will be summarized.

Germany, G.↗

Stellar Imager

The Stellar Imager (SI) is one of NASA's "Vision Missions" - concepts for future, space-based, strategic missions that could enormously increase our capabilities for observing the Cosmos. SI is designed as a UV/Optical Interferometer which will enable 0.1 milli-arcsecond (mas) spectral imaging of stellar surfaces and, via asteroseismology, stellar interiors and of the Universe in general. The ultra-sharp images of the Stellar Imager will revolutionize our view of many dynamic astrophysical processes by transforming point sources into extended sources, and snapshots into evolving views. SI, with a characteristic angular resolution of 0.1 milli-arcseconds at 2000 Angstroms, represents an advance in image detail of several hundred times over that provided by the Hubble Space Telescope. The Stellar Imager will zoom in on what today-with few exceptions - we only know as point sources, revealing processes never before seen, thus providing a tool as fundamental to astrophysics as the microscope is to the study of life on Earth. SI's science focuses on the role of magnetism in the Universe, particularly on magnetic activity on the surfaces of stars like the Sun. It's prime goal is to enable long-term forecasting of solar activity and the space weather that it drives, in support of the Living With a Star program in the Exploration Era. SI will also revolutionize our understanding of the formation of planetary systems, of the habitability and climatology of distant planets, and of many magneto-hydrodynamically controlled processes in the Universe. Stellar Imager is included as a "Flagship and Landmark Discovery Mission" in the 2005 Sun Solar System Connection (SSSC) Roadmap and as a candidate for a "Pathways to Life Observatory" in the Exploration of the Universe Division (EUD) Roadmap (May, 2005) and as such is a candidate mission for the 2025-2030 timeframe. An artist's drawing of the current "baseline" concept for SI is presented.

Carpenter, Kenneth↗

Imaging spectrometer/camera having convex grating

An imaging spectrometer has fore-optics coupled to a spectral resolving system with an entrance slit extending in a first direction at an imaging location of the fore-optics for receiving the image, a convex diffraction grating for separating the image into a plurality of spectra of predetermined wavelength ranges; a spectrometer array for detecting the spectra; and at least one concave sperical mirror concentric with the diffraction grating for relaying the image from the entrance slit to the diffraction grating and from the diffraction grating to the spectrometer array. In one embodiment, the spectrometer is configured in a lateral mode in which the entrance slit and the spectrometer array are displaced laterally on opposite sides of the diffraction grating in a second direction substantially perpendicular to the first direction. In another embodiment, the spectrometer is combined with a polychromatic imaging camera array disposed adjacent said entrance slit for recording said image.

Reininger, Francis M.↗

Image processing for hazard recognition in on-board weather radar

A method of providing weather radar images to a user includes obtaining radar image data corresponding to a weather radar image to be displayed. The radar image data is image processed to identify a feature of the weather radar image which is potentially indicative of a hazardous weather condition. The weather radar image is displayed to the user along with a notification of the existence of the feature which is potentially indicative of the hazardous weather condition. Notification can take the form of textual information regarding the feature, including feature type and proximity information. Notification can also take the form of visually highlighting the feature, for example by forming a visual border around the feature. Other forms of notification can also be used.

Kelly, Wallace E.↗

A Novel 24 GHz One-Shot, Rapid and Portable Microwave Imaging System

Development of microwave and millimeter wave imaging systems has received significant attention in the past decade. Signals at these frequencies penetrate inside of dielectric materials and have relatively small wavelengths. Thus. imaging systems at these frequencies can produce images of the dielectric and geometrical distributions of objects. Although there are many different approaches for imaging at these frequencies. they each have their respective advantageous and limiting features (hardware. reconstruction algorithms). One method involves electronically scanning a given spatial domain while recording the coherent scattered field distribution from an object. Consequently. different reconstruction or imaging techniques may be used to produce an image (dielectric distribution and geometrical features) of the object. The ability to perform this accurate~v and fast can lead to the development of a rapid imaging system that can be used in the same manner as a video camera. This paper describes the design of such a system. operating at 2-1 GHz. using modulated scatterer technique applied to 30 resonant slots in a prescribed measurement domain.

Ghasr, M. T.↗

Stereoscopic Imaging in Hypersonics Boundary Layers using Planar Laser-Induced Fluorescence

Stereoscopic time-resolved visualization of three-dimensional structures in a hypersonic flow has been performed for the first time. Nitric Oxide (NO) was seeded into hypersonic boundary layer flows that were designed to transition from laminar to turbulent. A thick laser sheet illuminated and excited the NO, causing spatially-varying fluorescence. Two cameras in a stereoscopic configuration were used to image the fluorescence. The images were processed in a computer visualization environment to provide stereoscopic image pairs. Two methods were used to display these image pairs: a cross-eyed viewing method which can be viewed by naked eyes, and red/blue anaglyphs, which require viewing through red/blue glasses. The images visualized three-dimensional information that would be lost if conventional planar laser-induced fluorescence imaging had been used. Two model configurations were studied in NASA Langley Research Center's 31-Inch Mach 10 Air Wind tunnel. One model was a 10 degree half-angle wedge containing a small protuberance to force the flow to transition. The other model was a 1/3-scale, truncated Hyper-X forebody model with blowing through a series of holes to force the boundary layer flow to transition to turbulence. In the former case, low flowrates of pure NO seeded and marked the boundary layer fluid. In the latter, a trace concentration of NO was seeded into the injected N2 gas. The three-dimensional visualizations have an effective time resolution of about 500 ns, which is fast enough to freeze this hypersonic flow. The 512x512 resolution of the resulting images is much higher than high-speed laser-sheet scanning systems with similar time response, which typically measure 10-20 planes.

Danehy, Paul M.↗