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In this article we describe the image compression scheme of the Galileo spacecraft and other downstream signal processing algorithms that enable efficient and robust transmission of data to Earth.
Symmetrical phase-only filtering (SPOF) can be exploited to obtain substantial improvements in the results of data processing in particle-image velocimetry (PIV). In comparison with traditional PIV data processing, SPOF PIV data processing yields narrower and larger amplitude correlation peaks, thereby providing more-accurate velocity estimates. The higher signal-to-noise ratios associated with the higher amplitude correlation peaks afford greater robustness and reliability of processing. SPOF also affords superior performance in the presence of surface flare light and/or background light. SPOF algorithms can readily be incorporated into pre-existing algorithms used to process digitized image data in PIV, without significantly increasing processing times. A summary of PIV and traditional PIV data processing is prerequisite to a meaningful description of SPOF PIV processing. In PIV, a pulsed laser is used to illuminate a substantially planar region of a flowing fluid in which particles are entrained. An electronic camera records digital images of the particles at two instants of time. The components of velocity of the fluid in the illuminated plane can be obtained by determining the displacements of particles between the two illumination pulses. The objective in PIV data processing is to compute the particle displacements from the digital image data. In traditional PIV data processing, to which the present innovation applies, the two images are divided into a grid of subregions and the displacements determined from cross-correlations between the corresponding sub-regions in the first and second images. The cross-correlation process begins with the calculation of the Fourier transforms (or fast Fourier transforms) of the subregion portions of the images. The Fourier transforms from the corresponding subregions are multiplied, and this product is inverse Fourier transformed, yielding the cross-correlation intensity distribution. The average displacement of the particles across a subregion results in a displacement of the correlation peak from the center of the correlation plane. The velocity is then computed from the displacement of the correlation peak and the time between the recording of the two images. The process as described thus far is performed for all the subregions. The resulting set of velocities in grid cells amounts to a velocity vector map of the flow field recorded on the image plane. In traditional PIV processing, surface flare light and bright background light give rise to a large, broad correlation peak, at the center of the correlation plane, that can overwhelm the true particle- displacement correlation peak. This has made it necessary to resort to tedious image-masking and background-subtraction procedures to recover the relatively small amplitude particle-displacement correlation peak. SPOF is a variant of phase-only filtering (POF), which, in turn, is a variant of matched spatial filtering (MSF). In MSF, one projects a first image (denoted the input image) onto a second image (denoted the filter) as part of a computation to determine how much and what part of the filter is present in the input image. MSF is equivalent to cross-correlation. In POF, the frequency-domain content of the MSF filter is modified to produce a unitamplitude (phase-only) object. POF is implemented by normalizing the Fourier transform of the filter by its magnitude. The advantage of POFs is that they yield correlation peaks that are sharper and have higher signal-to-noise ratios than those obtained through traditional MSF. In the SPOF, these benefits of POF can be extended to PIV data processing. The SPOF yields even better performance than the POF approach, which is uniquely applicable to PIV type image data. In SPOF as now applied to PIV data processing, a subregion of the first image is treated as the input image and the corresponding subregion of the second image is treated as the filter. The Fourier transforms from both the firs and second- image subregions are normalized by the square roots of their respective magnitudes. This scheme yields optimal performance because the amounts of normalization applied to the spatial-frequency contents of the input and filter scenes are just enough to enhance their high-spatial-frequency contents while reducing their spurious low-spatial-frequency content. As a result, in SPOF PIV processing, particle-displacement correlation peaks can readily be detected above spurious background peaks, without need for masking or background subtraction.
A new type of image detector has been designed to simultaneously analyze the polarization of light at all picture elements in a scene. The Integrated Dual Imaging Detector (IDID) consists of a polarizing beamsplitter bonded to a charge-coupled device (CCD), with signal-analysis circuitry and analog-to-digital converters, all integrated on a silicon chip. It should be capable of 1:10(exp 4) polarization discrimination. The IDID should simplify the design and operation of imaging polarimeters and spectroscopic imagers used, for example, in atmospheric and solar research. Innovations in the IDID include (1) two interleaved 512 x 1024-pixel imaging arrays (one for each polarization plane); (2) large dynamic range (well depth of 10(exp 6) electrons per pixel); (3) simultaneous readout of both images at 10 million pixels per second each; (4) on-chip analog signal processing to produce polarization maps in real time; (5) on-chip 10-bit A/D conversion. When used with a lithium-niobate Fabry-Perot etalon or other color filter that can encode spectral information as polarization, the IDID can collect and analyze simultaneous images at two wavelengths. Precise photometric analysis of molecular or atomic concentrations in the atmosphere is one suggested application. When used in a solar telescope, the IDID will charge the polarization, which can then be converted to maps of the vector magnetic fields on the solar surface.
Criteria and recommended practices for the design of the spaceborne elements of electronic imaging systems are presented. A spaceborne electronic imaging system is defined as a device that collects energy in some portion of the electromagnetic spectrum with detector(s) whose direct output is an electrical signal that can be processed (using direct transmission or delayed transmission after recording) to form a pictorial image. This definition encompasses both image tube systems and scanning point-detector systems. The intent was to collect the design experience and recommended practice of the several systems possessing the common denominator of acquiring images from space electronically and to maintain the system viewpoint rather than pursuing specialization in devices. The devices may be markedly different physically, but each was designed to provide a particular type of image within particular limitations. Performance parameters which determine the type of system selected for a given mission and which influence the design include: Sensitivity, Resolution, Dynamic range, Spectral response, Frame rate/bandwidth, Optics compatibility, Image motion, Radiation resistance, Size, Weight, Power, and Reliability.
This innovation is a system that augments human vision through a technique called "Sensing Super-position" using a Visual Instrument Sensory Organ Replacement (VISOR) device. The VISOR device translates visual and other sensors (i.e., thermal) into sounds to enable very difficult sensing tasks. Three-dimensional spatial brightness and multi-spectral maps of a sensed image are processed using real-time image processing techniques (e.g. histogram normalization) and transformed into a two-dimensional map of an audio signal as a function of frequency and time. Because the human hearing system is capable of learning to process and interpret extremely complicated and rapidly changing auditory patterns, the translation of images into sounds reduces the risk of accidentally filtering out important clues. The VISOR device was developed to augment the current state-of-the-art head-mounted (helmet) display systems. It provides the ability to sense beyond the human visible light range, to increase human sensing resolution, to use wider angle visual perception, and to improve the ability to sense distances. It also allows compensation for movement by the human or changes in the scene being viewed.
An apparatus and method for real-time visualization of particulate matter suspended in a static or flowing fluid and fluid flow patterns in a pipe, tube, conduit, or other container, are described. Ultrasonic scanning and detection of scattered sound from the particles in the fluid create a real-time image of the particles, or of flow patterns in the liquid. A mechanical wobbler directs a piezoelectric transducer over a chosen angle in an oscillatory manner. The transducer is operated in a pulse-echo mode wherein the same transducer detects the return signal from the target region through which particles are passing and/or a flow is present. The pulse-echo measurements are made rapidly and continuously during a single sweep of the transducer over the chosen angle. Received signals are processed in the ultrasound scanner electronics module and displayed as an image in real-time.
The extracellular matrix (ECM) is a complex network of biomolecules that plays an integral role in the structure, processes, and signaling mechanisms of cells and tissues. Identifying and quantifying changes in these matrix components provides insight into the mechanisms behind specific tissue remodeling processes; however, quantifying these changes is challenging due to difficult imaging conditions, complexity of the ECM, and the subtlety of these changes. Current imaging techniques allow us to visualize these critical remodeling events and developments in image analysis have employed a combination of analysis software and machine learning techniques to improve the efficiency and accuracy with which features are measured. Although image analysis has seen much improvement in recent years, there has been no technique developed to address ambiguity in feature edges in electron microscopy images. Presented here is a new machine learning-based workflow for the analysis of microscopy images named FIRM (Feature Identification from Raw Microscopy) that uses a random forest classifier to identify ECM features of interest and generate binary segmentation masks for quantification with ImageJ-FIJI. FIRM performed with an F1 score of 0.794 and greater than 80% accuracy for number and size of features detected. FIRM had similar deviation from the ground truth in the number of identified fibrils, fibril size, and size distributions when compared to human analyses. The results suggest that FIRM performs as well as manual analysis and requires a fraction of the time. This analysis technique is more efficient, eliminates user bias, and can be easily optimized to identify a variety of features, making it useful for any discipline requiring image analysis.
The present invention presents an optical encoder with increased conversion rates. Improvement in the conversion rate is a result of combining changes in the pattern recognition encoder's scale pattern with an image sensor readout technique which takes full advantage of those changes, and lends itself to operation by modern, high-speed, ultra-compact microprocessors and digital signal processors (DSP) or field programmable gate array (FPGA) logic elements which can process encoder scale images at the highest speeds. Through these improvements, all three components of conversion time (reciprocal conversion rate)--namely exposure time, image readout time, and image processing time--are minimized.
A novel technique is presented to image stray signals in RCS measurement ranges. In this technique, the scattered fields of a flat plate in the diagonal plane are measured in a range for various frequencies and look angles. The scattered field data is then processed to generate an inverse synthetic aperture radar (ISAR) image of the diagonal flat plate. It is shown that scattering mechanisms associated with various stray signals can be identified by using the ISAR image. This leads to better understanding of the range and possible chamber improvements. Scattering mechanisms as small as 90 dB below the plate broadside scattered field level have been observed in the image domain due to the high directivity and low sidelobe characteristics associated with the diagonal flat plate backscattered fields. The results obtained from evaluating the two compact range facilities at The Ohio State University ElectroScience Laboratory are presented to illustrate the virtues of this new range evaluation technique.
Understanding structure–property relationships is essential for advancing technologies based on thin films. X-ray pair distribution function (PDF) analysis can access relevant atomic structure details spanning local-, mid- and long-range structure. While X-ray PDF has been adapted for thin films on amorphous substrates, measurements on single-crystal substrates are necessary to accurately determine structure origins for some thin film materials, especially those for which the substrate changes the accessible structure and properties. However, when measuring films on single-crystal substrates, high-intensity anisotropic Bragg spots saturate 2D detector images, overshadowing the thin films' isotropic scattering signal. This renders previous data processing methods for films on amorphous substrates unsuitable for films on single-crystal substrates. To address this measurement need, we developed IsoDAT2D, an innovative data processing approach using unsupervised machine learning algorithms. The program combines dimensionality reduction and clustering algorithms to separate thin film and single-crystal substrate X-ray scattering signals. We use SimDAT2D , a program we developed to generate simulated thin film data, to validate IsoDAT2D . Here we also use IsoDAT2D to isolate X-ray total scattering signal from a thin film on a single-crystal substrate. The resulting PDF data are compared with similar data processed using previous methods, especially substrate subtraction for single-crystal and amorphous substrates. PDF data from IsoDAT2D -identified X-ray total scattering data are significantly better than from single-crystal substrate subtraction, but not as reliable as PDF data from amorphous substrate subtraction. With IsoDAT2D , there are new opportunities to expand PDF to a wider variety of thin films, including those on single-crystal substrates, with which new structure–property relationships can be elucidated to enable fundamental understanding and technological advances.
The fate of migrating insects that encounter rainfall in flight is a critical consideration when modelling insect movement, but few field observations of this common phenomenon have ever been collected due to the logistical challenges of witnessing these encounters. Operational cloud radars have been deployed around the world by meteorological agencies to study precipitation physics, and as a byproduct, provide a rich database of insect observations that is freely available to researchers. Although considered unwanted ‘clutter’ by the meteorologists who collect the data, the analysis method presented here enables ecologists to delineate co-occurring signals from insects and raindrops. We present a method that uses image processing techniques on cloud radar velocity spectra to examine the fate of migrating insects when they encounter precipitation. By analysing velocity spectra, we can distinguish flying insects from falling rain and compare the relative density of insects in flight before, during and after the rainfall. We demonstrate the method on a case of insect migration in Oklahoma, USA. Using this method, we show the first reconstructed images of migrating insect layers in flight during rainfall. Our analysis shows that mild to moderate rainfall diminishes the number of insects aloft but does not cause full termination of migratory flight, as has previously been suggested. We hope this technique will spur further investigations of how changing weather conditions impact insect migration, and enable some of the first of such studies in regions of the world that are underrepresented in the literature.
Review of the results of the application of an advanced signal-processing technique, called time delay spectrometry, in obtaining soft tissue transmission images by transmission ultrasonography, both in vivo and in vitro. The presented results include amplitude ultrasound pictures and phase ultrasound pictures obtained by this technique. While amplitude ultrasonographs of tissue are closely analogous to X-ray pictures in that differential absorption is imaged, phase ultrasonographs represent an entirely new source of information based on differential time of propagation. Thus, a new source of information is made available for detailed analysis.
Acousto-electric devices for electronic imaging of light are discussed. These devices are more versatile than line scan imaging devices in current use. They have the capability of presenting the image information in a variety of modes. The image can be read out in the conventional line scan mode. It can be read out in the form of the Fourier, Hadamard, or other transform. One can take the transform along one direction of the image and line scan in the other direction, or perform other combinations of image processing functions. This is accomplished by applying the appropriate electrical input signals to the device. Since the electrical output signal of these devices can be detected in a synchronous mode, substantial noise reduction is possible
Proposed system stabilizes jittering television image and/or measures jitter to extract information on motions of objects in image. Alternative version, system controls lateral motion on camera to generate stereoscopic views to measure distances to objects. In another version, motion of camera controlled to keep object in view. Heart of system is digital image-data processor called "jitter-miser", which includes frame buffer and logic circuits to correct for jitter in image. Signals from motion sensors on camera sent to logic circuits and processed into corrections for motion along and across line of sight.
Under the Aircraft Structural Integrity program, Langley Research Center and Stress Photonics developed an infrared-based stress measurement system for use in nondestructive evaluation of materials and structures. Stress Photonics commercialized the technology in the DeltaTherm 1000 system, used to compare designs and detect cracks in structures, especially for aging aircraft and bridges. The system combines digital signal processing technology with a special infrared camera to provide instantaneous thermal images and live differential images.
During the early stages of the NASA Scientific Data Purchase (SDP) program, three approximately equal vertical stripes were observable in the IKONOS imagery of highly spatially uniform sites. Although these effects appeared to be less than a few percent of the mean signal, several investigators requested new imagery. Over time, Space Imaging updated its processing to minimize these artifacts. This however, produced differences in Space Imaging products derived from archive imagery processed at different times. Imagery processed before 2/22/01 is processed with one set of coefficients, while imagery processed after that date requires another set. Space Imaging produces its products from raw imagery, so changes in the ground processing over time can change the delivered digital number (DN) values, even for identical orders of a previously acquired scene. NASA Stennis initiated studies to investigate the magnitude and changes in these artifacts over the lifetime of the system and before and after processing updates.
A method for generating color video signals representative of color images of a scene includes the following steps: focusing light from the scene on an electronic image sensor via a filter having a tri-color filter pattern; producing, from outputs of the sensor, first and second relatively low resolution luminance signals; producing, from outputs of the sensor, a relatively high resolution luminance signal; producing, from a ratio of the relatively high resolution luminance signal to the first relatively low resolution luminance signal, a high band luminance component signal; producing, from outputs of the sensor, relatively low resolution color component signals; and combining each of the relatively low resolution color component signals with the high band luminance component signal to obtain relatively high resolution color component signals.
Long-term spaceflight may induce a variety of harmful effects in astronauts, resulting in altered motor and cognitive behavior. The stresses experienced by humans in space - most significantly weightlessness (microgravity) and cosmic radiation - are difficult to accurately simulate on Earth. In fact, prolonged and concomitant exposure to microgravity and cosmic radiation can only be studied in space. Behavioral studies in space have focused on model organisms, including Drosophila melanogaster. Drosophila is often used due to its short life span and generational cycle, small size, and ease of maintenance. Additionally, the well-characterized genetics of Drosophila behavior on Earth can be applied to the analysis of results from spaceflights, provided that the behavior in space is accurately recorded. In 2001, the BioExplorer project introduced a low-cost option for researchers: the small satellite. While this approach enabled multiple inexpensive launches of biological experiments, it also imposed stringent restrictions on the monitoring systems in terms of size, mass, data bandwidth, and power consumption. Suggested parameters for size are on the order of 100 mm3 and 1 kg mass for the entire payload. For Drosophila behavioral studies, these engineering requirements are not met by commercially available systems. One system that does meet many requirements for behavioral studies in space is the actimeter. Actimeters use infrared light gates to track the number of times a fly crosses a boundary within a small container (3x3x40 mm). Unfortunately, the apparatus needed to monitor several flies at once would be larger than the capacity of the small satellite. A system is presented, which expands on the actimeter approach to achieve a highly compact, low-power, ultra-low bandwidth solution for simultaneous monitoring of the behavior of multiple flies in space. This also provides a simple, inexpensive alternative to the current systems for monitoring Drosophila populations in terrestrial experiments, and could be especially useful in field experiments in remote locations. Two practical limitations of the system should be noted: first, only walking flies can be observed - not flying - and second, although it enables population studies, tracking individual flies within the population is not currently possible. The system used video recording and an analog circuit to extract the average light changes as a function of time. Flies were held in a 5-cm diameter Petri dish and illuminated from below by a uniform light source. A miniature, monochrome CMOS (complementary metal-oxide semiconductor) video camera imaged the flies. This camera had automatic gain control, and this did not affect system performance. The camera was positioned 5-7 cm above the Petri dish such that the imaging area was 2.25 sq cm. With this basic setup, still images and continuous video of 15 flies at one time were obtained. To reduce the required data bandwidth by several orders of magnitude, a band-pass filter (0.3-10 Hz) circuit compressed the video signal and extracted changes in image luminance over time. The raw activity signal output of this circuit was recorded on a computer and digitally processed to extract the fly movement "events" from the waveform. These events corresponded to flies entering and leaving the image and were used for extracting activity parameters such as inter-event duration. The efficacy of the system in quantifying locomotor activity was evaluated by varying environmental temperature, then measuring the activity level of the flies.