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Instructional material describing a methodology of remote sensing data interpretation and examples of applicatons to land use survey are presented. The image interpretation elements are discussed for different types of sensor systems: aerial photographs, radar, and MSS/LANDSAT. Visual and automatic LANDSAT image interpretation is emphasized.
Status is given of an applications investigation on the potential for using an expert system shell for classification and retrieval of high resolution, digital, color space shuttle closeout photography. This NASA funded activity has focused on the use of integrated information technologies to intelligently classify and retrieve still imagery from a large, electronically stored collection. A space shuttle processing problem is identified, a working prototype system is described, and commercial applications are identified. A conclusion reached is that the developed system has distinct advantages over the present manual system and cost efficiencies will result as the system is implemented. Further, commercial potential exists for this integrated technology.
Fly through the ocean at breakneck speed. Tour the moon. Even swim safely in the boiling sun. You can do these things and more in a 17 minute virtual journey through Earth and space. The trek is by way of colorful scientific visualizations developed by the NASA/Goddard Space Flight Center's Scientific Visualization Studio and the NASA HPCC Earth and Space Science Project investigators. Various styles of electronic music and lay-level narration provide the accompaniment.
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Spectron has been deeply involved in the development and use of a wide variety of particle and flow diagnostic, electro optical instruments. Holography and imaging systems have played an important role in this work, but the extraction of data from images and holograms have always presented a limit to their use. Systems and techniques were devised to speed up and automate the extraction of data from holographic and conventional interferograms, particle images and holograms, and other types of optical flow visualization techniques. An IBM/AI based image analyzer was developed that is capable of automatically analyzing many useful image types including interferograms. A key feature of this system is the low total cost of the required hardware. In the particle field work, a commercial diffraction field analyzer was adopted to the image reconstructed from a hologram. This could expand the use of holography in particle diagnostics greatly.
Shannon's mathematical theory of communication is extended to image gathering. Expressions are obtained for the total information that is received with a single image-gathering channel and with parallel channels. It is concluded that the aliased signal components carry information even though these components interfere with the within-passband components in conventional image gathering and restoration, thereby degrading the fidelity and visual quality of the restored image. An examination of the expression for minimum mean-square-error, or Wiener-matrix, restoration from parallel image-gathering channels reveals a method for unscrambling the within-passband and aliased signal components to restore spatial frequencies beyond the sampling passband out to the spatial frequency response cutoff of the optical aperture.
Topographic measurements of sea surface elevation collected by the Surface Contour Radar (SCR) during NASA's Shuttle Imaging Radar (SIR-B) experiment are plotted as three dimensional surface plots to observe wave height variance along the track of a P-3 aircraft. Ocean wave spectra were computed from rotating altimeter measurements acquired by the Radar Ocean Wave Spectrometer (ROWS). Fourier power spectra computed from SIR-B synthetic aperture radar (SAR) images of the ocean are compared to ROWS surface wave spectra. Fourier inversion of SAR spectra, after subtraction of spectral noise and modeling of wave height modulation, yields topography similar to direct measurements made by SCR. Visual perspectives on the SCR and SAR ocean data are compared. Threshold distinctions between surface elevation and texture modulations of SAR data are considered within the context of a dynamic statistical model of rough surface scattering. The result of these endeavors is insight as to the physical mechanism governing the imaging of ocean waves with SAR.
The current X-ray systems used by airport security personnel for the detection of contraband, and objects such as knives and guns that can impact the security of a flight, have limited effect because of the limited display quality of the X-ray images. Since the displayed images do not possess optimal contrast and sharpness, it is possible for the security personnel to miss potentially hazardous objects. This problem is also common to other disciplines such as medical X-rays, and can be mitigated, to a large extent, by the use of state-of-the-art image processing techniques to enhance the contrast and sharpness of the displayed image. The NASA Langley Research Centers Visual Information Processing Group has developed an image enhancement technology that has direct applications to this problem of inadequate display quality. Airport security X-ray imaging systems would benefit considerably by using this novel technology, making the task of the personnel who have to interpret the X-ray images considerably easier, faster, and more reliable. This improvement would translate into more accurate screening as well as minimizing the screening time delays to airline passengers. This technology, Retinex, has been optimized for consumer applications but has been applied to medical X-rays on a very preliminary basis. The resultant technology could be incorporated into a new breed of commercial x-ray imaging systems which would be transparent to the screener yet allow them to see subtle detail much more easily, reducing the amount of time needed for screening while greatly increasing the effectiveness of contraband detection and thus public safety.
This slide presentation reviews the use of "soft computing" which differs from "hard computing" in that it is more tolerant of imprecision, partial truth, uncertainty, and approximation and its use in image analysis. Soft computing provides flexible information processing to handle real life ambiguous situations and achieve tractability, robustness low solution cost, and a closer resemblance to human decision making. Several systems are or have been developed: Fuzzy Reasoning Edge Detection (FRED), Fuzzy Reasoning Adaptive Thresholding (FRAT), Image enhancement techniques, and visual/pattern recognition. These systems are compared with examples that show the effectiveness of each. NASA applications that are reviewed are: Real-Time (RT) Anomaly Detection, Real-Time (RT) Moving Debris Detection and the Columbia Investigation. The RT anomaly detection reviewed the case of a damaged cable for the emergency egress system. The use of these techniques is further illustrated in the Columbia investigation with the location and detection of Foam debris. There are several applications in commercial usage: image enhancement, human screening and privacy protection, visual inspection, 3D heart visualization, tumor detections and x ray image enhancement.
This research is based on the exploration of tectonic patterns on Titan from a global perspective. Several moons in the outer solar system display patterns of surface tectonic features that imply global stress fields driven or modified by global forces. Patterns such as these are seen in Europa's tidally induced fracture patterns, Enceladus's tiger stripes, and Ganymede's global expansion induced normal fault bands. Given its proximity to Saturn, as well as its eccentric orbit, tectonic features and global stresses may be present on Titan as well. Titan displays possible tectonic structures, such as mountain chains along its equator (Radebaugh et al. 2007), as well as the unexplored dark linear streaks termed virgae by the IAU. Imaged by Cassini with the RADAR instrument, mountain chains near the equator are observed with a predominante east-west orientation (Liu et al. 2012, Mitri et al. 2010). Orientations such as these can be explained by modifications in the global tidal stress field induced by global contraction followed by rotational spin-up. Also, due to Titan's eccentric orbit, its current rotation rate may be in an equilibrium between tidal spin-up near periapsis and spin-down near apoapsis (Barnes and Fortney 2003). Additional stress from rotational spin-up provides an asymmetry to the stress field. This, combined with an isotropic stress from radial contraction, favors the formation of equatorial mountain chains in an east-west direction. The virgae, which have been imaged by Cassini with both the Visual and Infrared Mapping Spectrometer (VIMS) and Imaging Science Subsystem (ISS) instruments, are located predominately near 30 degrees latitude in either hemisphere. Oriented with a pronounced elongation in the east-west direction, all observed virgae display similar characteristics: similar relative albedos as the surrounding terrain however darkened with an apparent neutral absorber, broken-linear or rounded sharp edges, and connected, angular elements with distinct, linear edges. Virgae imaged during northern latitude passes are oriented with their long dimensions toward Titan's antiSaturn point. If the virgae are of tectonic origin, for instance if the turn out to be i.e. grabens, they could serve as markers to Titan's global stress field. Using them in this way allows for a mapping of global tectonic patterns. These patterns will be tested for consistency against the various sources of global stress and orientations of mountain chains. By determining what drives Titan's tectonics globally, we will be able to place Titan within the context of the other outer planet icy satellites.
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.
Comparative statistics were presented on the capability of LANDSAT-1 and three of the Skylab remote sensing systems (S-190A, S-190B, S-192) for the recognition and inventory of analogous natural vegetations and landscape features important in resource allocation and management. Two analogous regions presenting vegetational zonation from salt desert to alpine conditions above the timberline were observed, emphasizing the visual interpretation mode in the investigation. An hierarchical legend system was used as the basic classification of all land surface features. Comparative tests were run on image identifiability with the different sensor systems, and mapping and interpretation tests were made both in monocular and stereo interpretation with all systems except the S-192. Significant advantage was found in the use of stereo from space when image analysis is by visual or visual-machine-aided interactive systems. Some cost factors in mapping from space are identified. The various image types are compared and an operational system is postulated.
The central-western part of Rio Grande do Sul Shield was geologically mapped to test the use of MSS-LANDSAT data in the study of mineralized regions. Visual interpretation of the images a the scale of 1:500,000 consisted, in the identification and analysis of the different tonal and textural patterns in each spectral band. After the structural geologic mapping of the area, using visual interpretation techniques, the statistical data obtained were evaluated, specially data concerning size and direction of fractures. The IMAGE-100 system was used to enlarge and enhance certain imagery. The LANDSAT MSS data offer several advantages over conventional white and black aerial photographs for geological studies. Its multispectral characteristic (band 6 and false color composition of bands 4, 5 and 7 were best suitable for the study). Coverage of a large imaging area of about 35,000 sq km, giving a synoptical view, is very useful for perceiving the regional geological setting.
The following details recent efforts undertaken at the NASA Ames Unitary Plan wind tunnels to design and deploy an advanced, production-level infrared (IR) flow visualization data system. Highly sensitive IR cameras, coupled with in-line image processing, have enabled the visualization of wind tunnel model surface flow features as they develop in real-time. Boundary layer transition, shock impingement, junction flow, vortex dynamics, and buffet are routinely observed in both transonic and supersonic flow regimes all without the need of dedicated ramps in test section total temperature. Successful measurements have been performed on wing-body sting mounted test articles, semi-span floor mounted aircraft models, and sting mounted launch vehicle configurations. The unique requirements of imaging in production wind tunnel testing has led to advancements in the deployment of advanced IR cameras in a harsh test environment, robust data acquisition storage and workflow, real-time image processing algorithms, and evaluation of optimal surface treatments. The addition of a multi-camera IR flow visualization data system to the Ames UPWT has demonstrated itself to be a valuable analyses tool in the study of new and old aircraft/launch vehicle aerodynamics and has provided new insight for the evaluation of computational techniques.
A real time model of the visible output from a 94 GHz sensor, based on a radiometric simulation of the sensor, was developed. A sequence of images as seen from an aircraft as it approaches for landing was simulated using this model. Thirty frames from this sequence of 200 x 200 pixel images were analyzed to identify and track objects in the image using the Cantata image processing package within the visual programming environment provided by the Khoros software system. The image analysis operations are described.
The human visual system comprises layers of networks which sample, process, and code images. Understanding these networks is a valuable means of understanding human vision and of designing autonomous vision systems based on network processing. Ames Research Center has an ongoing program to develop computational models of such networks. The models predict human performance in detection of targets and in discrimination of displayed information. In addition, the models are artificial vision systems sharing properties with biological vision that has been tuned by evolution for high performance. Properties include variable density sampling, noise immunity, multi-resolution coding, and fault-tolerance. The research stresses analysis of noise in visual networks, including sampling, photon, and processing unit noises. Specific accomplishments include: models of sampling array growth with variable density and irregularity comparable to that of the retinal cone mosaic; noise models of networks with signal-dependent and independent noise; models of network connection development for preserving spatial registration and interpolation; multi-resolution encoding models based on hexagonal arrays (HOP transform); and mathematical procedures for simplifying analysis of large networks.
Recommendations for minimal in-flight capabilities: Retinal Imaging - provide in-flight capability for the visual monitoring of ocular health (specifically, imaging of the retina and optic nerve head) with the capability of downlinking video/still images. Tonometry - provide more accurate and reliable in-flight capability for measuring intraocular pressure. Ultrasound - explore capabilities of current on-board system for monitoring ocular health. We currently have limited in-flight capabilities on board the International Space Station for performing an internal ocular health assessment. Visual Acuity, Direct Ophthalmoscope, Ultrasound, Tonometry(Tonopen):
A two phase sampling method and the optimal sampling segment dimensions for the estimation of sugar cane cultivated area were developed. This technique employs visual interpretations of LANDSAT images and panchromatic aerial photographs considered as the ground truth. The estimates, as a mean value of 100 simulated samples, represent 99.3% of the true value with a CV of approximately 1%; the relative efficiency of the two phase design was 157% when compared with a one phase aerial photographs sample.