Independent stochastic processes are used to generate in parallel irregular tessellations of an image. Recursive application of the procedure yields a multiresolution hierarchy adapted to the content of the image. the...
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ISBN:
(纸本)0818620625
Independent stochastic processes are used to generate in parallel irregular tessellations of an image. Recursive application of the procedure yields a multiresolution hierarchy adapted to the content of the image. the hierarchy is similar to traditional image pyramids: its height is of log (image-size) order, but by being adapted to the input, it eliminates the artifacts frequently present in the latter. the output obtained at the apex of the hierarchy can be used for fast image analysis. the technique was applied to connected component labeling (labeled images) and segmentation (gray-level images).
the authors present a parallel 3-D image segmentation algorithm which, through the use of α-partitioning and volume filtering, segments 3-D images such that the gray-level variation within each volume can be describe...
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ISBN:
(纸本)0818620625
the authors present a parallel 3-D image segmentation algorithm which, through the use of α-partitioning and volume filtering, segments 3-D images such that the gray-level variation within each volume can be described by a regression model. Experimental results indicate that the use of discontinuity locations in α-partitioning can greatly assist the segmentation of 3-D images. It is also shown that the use of volume filters in removing incorrect partitions permits quick segmentation of 3-D images into functional descriptions for each volume. these two characteristics enabled the parallel 3-D image segmentation algorithm to produce fair segmentation results with large savings in computation time.
the Multiport Array Receptor (MAR), a system which combines optical sensing with integrated focal-plane processing capabilities, is described. Its central element is a photosensor array with hexagonal tesselation and ...
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the Multiport Array Receptor (MAR), a system which combines optical sensing with integrated focal-plane processing capabilities, is described. Its central element is a photosensor array with hexagonal tesselation and complex peripheral selection logic which provides parallel analog readout over prescribed areas. An external computing module performs real-time spatial convolution at multiple resolutions while a closed-loop microprogrammed controller addresses regions of interest and supervises communication between the camera and the host computer. this integrated image sensor and processor implements programmed sequences of instruction primitives and yields a complete state description of each processed pixel. It is capable of automatic edge tracking and returns lists of connected pixels.
the recovery of depth from defocused images is formulated as a 3-D image restoration problem. A defocused image is modeled as the combinatorial outcome of the depths and intensities of the volume elements (voxels) of ...
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ISBN:
(纸本)0818620625
the recovery of depth from defocused images is formulated as a 3-D image restoration problem. A defocused image is modeled as the combinatorial outcome of the depths and intensities of the volume elements (voxels) of an opaque 3-D object. A large depth-of-field image is used to constrain the intensities of the voxels. the depths of voxels are estimated from a highly defocused image by using simulated annealing to solve a constrained optimization problem. It is concluded that the method provides a framework for high-resolution depth recovery from defocused images. the method is computationally-intensive;however, it is amenable to parallelprocessing and is well suited for small field-of-interest applications.
A multimodal approach to the problem of velocity estimation is presented. It combines the advantages of the feature-based and gradient-based methods by making them cooperate in a single global motion estimator. the th...
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ISBN:
(纸本)0818620625
A multimodal approach to the problem of velocity estimation is presented. It combines the advantages of the feature-based and gradient-based methods by making them cooperate in a single global motion estimator. the theoretical framework is based on global Bayesian decision associated with Markov random field models. the proposed approach addresses, in parallel, the problem of velocity estimation and segmentation. Results on synthetic as well as on real-world image sequences are presented. Accurate motion measurement and detection of motion discontinuities with a surprisingly good quality have been obtained.
A specialized language, called Adapt, for local and global image processing on parallel processors is presented. Adapt is based on a split and merge model. the input image is split into sections, which are processed s...
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A specialized language, called Adapt, for local and global image processing on parallel processors is presented. Adapt is based on a split and merge model. the input image is split into sections, which are processed separately on different processors, and the results are merged using a function written by the user. this model is quite general; any image processing operation that can be computed from top to bottom or from bottom to top on an image can be computed with it. the use of Adapt is illustrated with several programs for important global operations, including histogram, Hough transform, minimum bounding rectangle, and connected components. A preliminary implementation of Adapt exists on the Carnegie Mellon Warp machine. Performance figures from this implementation are provided. A description of how Adapt can be implemented on other architectures is given.< >
A system for dynamic intelligent scheduling and control (DISC) of reconfigurable parallel processors is presented. the purpose of the system is to provide a rapid prototyping capability for computer vision/image proce...
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A system for dynamic intelligent scheduling and control (DISC) of reconfigurable parallel processors is presented. the purpose of the system is to provide a rapid prototyping capability for computer vision/image processing tasks. the scheduler particularly addresses the problems of algorithms with execution times that depend on the image data and processing scenarios that vary dynamically based on the input image. Since conventional scheduling methods cannot propose schedules for most masks of this type, a dynamic controller is used to schedule the task and reconfigure the machine on the fly. this dynamic scheduling system attempts to balance the overall processing scenario withthe needs of the individual routines that make up the task. the implementation of this system is discussed, with emphasis on the scheduling heuristics and the use of the system for prototyping computer vision/image processing tasks. Testing was done on a number of tasks that exercised different aspects of the scheduling strategy.< >
Toboggan contrast enhancement is a noniterative single-parameter, linear execution time method for selectively augmenting the contrast of multispectral images of arbitrary dimensionality. Toboggan enhancement followed...
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ISBN:
(纸本)0818620625
Toboggan contrast enhancement is a noniterative single-parameter, linear execution time method for selectively augmenting the contrast of multispectral images of arbitrary dimensionality. Toboggan enhancement followed by contrast segmentation is compared with adaptive smoothing, an iterative, multiple parameter, parallel approach that achieves similar results. the segmentation produced by toboggan enhancement followed by contrast segmentation appears equal in quality to that of very complex optimal regional growing segmentation methods. It is concluded that toboggan enhancement is easy to understand and manipulate and is applicable to any image (multispectral, multidimensional) for which one can define a function of local discontinuity at a pixel.
A semantic analysis approach is described in which diagrams are represented as collections of geometric objects. the fundamental organizing principle for these objects is the generalized equivalence relation (GER). Ex...
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ISBN:
(纸本)0818620625
A semantic analysis approach is described in which diagrams are represented as collections of geometric objects. the fundamental organizing principle for these objects is the generalized equivalence relation (GER). Examples include near, parallel, and aligned. these relations can be computed efficiently using Gossamer, a pyramidal data structure that allows spatially associative access to objects. Animate vision, in which the image is scanned either continuously or discontinuously, is used to mimic the efficient strategy used by humans to view diagrams. the system is implemented in Common Lisp and is being applied to data graphs and gene diagrams in the biological literature.
An iterative algorithm to increase image resolution is described. Examples are shown for low-resolution gray-level pictures, with an increase of resolution clearly observed after only a few iterations. the same method...
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An iterative algorithm to increase image resolution is described. Examples are shown for low-resolution gray-level pictures, with an increase of resolution clearly observed after only a few iterations. the same method can also be used for deblurring a single blurred image. the approach is based on the resemblance of the presented problem to the reconstruction of a 2-D object from its 1-D projections in computer-aided tomography. the algorithm performed well for both computer-simulated and real images and is shown, theoretically and practically, to converge quickly. the algorithm can be executed in parallel for faster hardware implementation.
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