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Systems and methods of x-ray backscatter radiography are provided. A single-sided, non-destructive imaging technique utilizing x-ray radiation to image subsurface features is disclosed, capable of scanning a region using a fan beam aperture and gathering data using rotational motion.
Computer image processing techniques have been applied to particle counting and sizing in electron microscope images. Distributions of particle sizes were computed for several images and compared to manually computed distributions. The results of these experiments indicate that automatic particle counting within a reasonable error and computer processing time is feasible. The significance of the results is that the tedious task of manually counting a large number of particles can be eliminated while still providing the scientist with accurate results.
Computed tomography imaging spectrometers ("CTIS"s) having color focal plane array detectors are provided. The color FPA detector may comprise a digital color camera including a digital image sensor, such as a Foveon X3.RTM. digital image sensor or a Bayer color filter mosaic. In another embodiment, the CTIS includes a pattern imposed either directly on the object scene being imaged or at the field stop aperture. The use of a color FPA detector and the pattern improves the accuracy of the captured spatial and spectral information.
Computed Tomography Imaging Spectrographs (CTISs), which are generally slitless or large-aperture spectrographs that observe a wide, dispersed field of view in multiple dispersion angles or diffraction orders, provide a unique opportunity to capture spectral information over an extended source, such as the Sun, but require software reconstruction techniques to be fully utilized. A useful data product that can be recovered from CTIS observations is intensity maps of solar features in single spectral lines. These intensity maps can then be used to determine temperature, density, abundance, and equilibrium properties of the emitting plasma. We apply the multiplicative algebraic reconstruction technique (MART) to example data from a variety of CTIS configurations to determine the capability and limitations of the method to return spectrally-pure maps. By completing this study, we aim to establish a path to derive requirements for CTIS instruments that rely on reconstruction techniques to meet their science objectives.
Computed tomography imaging spectrometers ("CTIS"s) having patterns for imposing spatial structure are provided. The pattern may be imposed either directly on the object scene being imaged or at the field stop aperture. The use of the pattern improves the accuracy of the captured spatial and spectral information.
Computer is provided with information concerning boundaries in total image. Gradient of each point in digitized image is calculated with aid of threshold technique; then there is invoked set of algorithms designed to reduce number of gradient elements and to retain only major ones for definition of contour.
Computer techniques for some enhancements of ERTS-1 images for Arizona geology mapping experiment in Colorado plateau
Enhanced depth of focus aids medical analysis. Computer image-processing system synthesizes sharply-focused composite picture from series of photomicrographs of same object taken at different depths. Computer rejects blured parts of each photomicrograph. Remaining in focus portions form focused composite. System used to study alveolar lung tissue and has applications in medicine and physical sciences.
Computer processing role in film scanning and digitizing for enhancing X ray and radioisotope scanner images in medical radiographs, discussing image noise reduction
This software computes the tomographic reconstruction of spatial-spectral data from raw detector images of the Computed-Tomography Imaging Spectrometer (CTIS), which enables transient-level, multi-spectral imaging by capturing spatial and spectral information in a single snapshot.
Two-domain method of computational classification of images requires less computation than other methods for computational recognition, matching, or classification of images or patterns. Does not require explicit computational matching of features, and incorporates human expertise without requiring translation of mental processes of classification into language comprehensible to computer. Conceived to "train" computer to analyze photomicrographs of microscope-slide specimens of leucocytes from human peripheral blood to distinguish between specimens from healthy and specimens from traumatized patients.
Computed radiography (CR) imaging plates and film are used in HEAF firing tanks and in the NDE group. The imaging plates allow for the creation of high-resolution digital images with flash X-ray (FXR). A typical treatment of flash X-ray radiographs is flat-field correction, where the image from an experiment is normalized by a “flat-field” or “bright-field” image. This flat-field image is taken in an identical configuration to the experimental image, but without the object or experiment in the field of view (FOV). This treatment reduces spatial effects from the FXR spot size and detector misalignment, as each pixel value in the corrected image represents a ratio of collected radiation with the object in FOV to the collected radiation without the object in FOV. One challenge in the creation of a corrected image is the misalignment of the CR plate or film pack between capturing the flat-field image and the experimental image. Fiducial structures can remedy this issue. Small (3.18mm) stainless steel ball bearings serve as good fiducial structures due to their small size and high radiographic contrast. Spheres are view-agnostic geometry, always presenting a circular cross section no matter the orientation. This process was developed for images from the flash X-ray testbed. The flash testbed was used to compare the X-ray transmission at different thicknesses of aluminum and copper step wedges. Each step wedge section is a rectangular shape, so evaluation is made much simpler if the rectangles are not rotated with respect to the image. This alignment process aligns the object and flat-field images together and leaves the rectangles of each step aligned with the image.
A high-performance computational imager based on integration of CMOS active pixel imager array with on-chip signal processing and control via a new column-parallel architecture is presented.
Computer vision has applications in object detection, image recognition and classification, and object tracking. One of the challenges of computer vision is the presence of useful information at multiple distance scales. Filtering techniques may sacrifice details at small scales in order to prioritize the analysis of large-scale features of the image. We present a strategy for coarse-graining multidimensional data while maintaining fine-grained detail for subsequent analysis. The algorithm is based on fixed-size block segmentation in the feature space. We apply this strategy to solve the long-standing challenge of detecting particle trajectories at the Large Hadron Collider in real time.
An independent geometry display program called IMAGE is presented. The use of the program permits the editing of geometric configurations and the monitoring of geometric perturbations.
This work relates to the generic problem of remote active imaging; that is, a source illuminates a target of interest and a receiver collects the scattered light off the target to obtain an image. Conventional imaging systems consist of an imaging lens and a high-resolution detector array [e.g., a CCD (charge coupled device) array] to register the image. However, conventional imaging systems for remote sensing require high-quality optics and need to support large detector arrays and associated electronics. This results in suboptimal size, weight, and power consumption. Computational ghost imaging (CGI) is a computational alternative to this traditional imaging concept that has a very simple receiver structure. In CGI, the transmitter illuminates the target with a modulated light source. A single-pixel (bucket) detector collects the scattered light. Then, via computation (i.e., postprocessing), the receiver can reconstruct the image using the knowledge of the modulation that was projected onto the target by the transmitter. This way, one can construct a very simple receiver that, in principle, requires no lens to image a target. Ghost imaging is a transverse imaging modality that has been receiving much attention owing to a rich interconnection of novel physical characteristics and novel signal processing algorithms suitable for active computational imaging. The original ghost imaging experiments consisted of two correlated optical beams traversing distinct paths and impinging on two spatially-separated photodetectors: one beam interacts with the target and then illuminates on a single-pixel (bucket) detector that provides no spatial resolution, whereas the other beam traverses an independent path and impinges on a high-resolution camera without any interaction with the target. The term ghost imaging was coined soon after the initial experiments were reported, to emphasize the fact that by cross-correlating two photocurrents, one generates an image of the target. In CGI, the measurement obtained from the reference arm (with the high-resolution detector) is replaced by a computational derivation of the measurement-plane intensity profile of the reference-arm beam. The algorithms applied to computational ghost imaging have diversified beyond simple correlation measurements, and now include modern reconstruction algorithms based on compressive sensing.
Computer graphics devices coupled with computers and carefully developed software provide new opportunities to achieve insight into the geometry and time evolution of scalar, vector, and tensor fields and to extract more information quickly and cheaply from the same image data. Two or more different fields which overlay in space can be calculated from the data (and the physics), then displayed from any perspective, and compared visually. The maximum regions of one field can be compared with the gradients of another. Time changing fields can also be compared. Images can be added, subtracted, transformed, noise filtered, frequency filtered, contrast enhanced, color coded, enlarged, compressed, parameterized, and histogrammed, in whole or section by section. Today it is possible to process multiple digital images to reveal spatial and temporal correlations and cross correlations. Data from different observatories taken at different times can be processed, interpolated, and transformed to a common coordinate system.
The computed-tomography imaging spectrometer (CTIS) captures a scene's spatial and spectral information without any type of scanning.