A projection-space approach for reconstruction from projections is presented. This approach uses the known convex support of the object both as a penalty term in a variational problem defined in projection-space and a...
A projection-space approach for reconstruction from projections is presented. This approach uses the known convex support of the object both as a penalty term in a variational problem defined in projection-space and as a guide to the specification of optimal smoothing coefficients that may vary spatially. Partial consistency of the sinogram is provided by including mass and center-of-mass constraints in the variational formulation. An outline of the general approach and calculations for a specific example are provided. computer simulations are provided for evaluation of the performance in this special case
We examine the tracking of 3-dimensional targets moving in a complex (e.g. highly textured) visual environment, which makes the application of methods relying on static segmentation and feature correspondence very pro...
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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 ...
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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.< >
Texture analysis algorithms that decompose images into oriented spatial frequency channels are studied. Optimality properties for texture segmentation filters are considered using idealized (narrowband) image texture ...
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Texture analysis algorithms that decompose images into oriented spatial frequency channels are studied. Optimality properties for texture segmentation filters are considered using idealized (narrowband) image texture models. The functional uncertainty of the channel filters is shown to define a tradeoff between spectral selectivity and accuracy in boundary localization that is optimized by the 2-D Gabor functions. The idealized texture model is then relaxed to analyze the effects of textural perturbations interpreted as localized amplitude and phase variations on the segmentation. The effects of these perturbations are found to be effectively ameliorated with postdetection smoothing.< >
Visual pattern image coding (VPIC) is a flexible image coding device offering excellent visual fidelity at high compression ratios with unprecedented, extremely low coding complexity. Hierarchical visual pattern image...
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Visual pattern image coding (VPIC) is a flexible image coding device offering excellent visual fidelity at high compression ratios with unprecedented, extremely low coding complexity. Hierarchical visual pattern image coding (HVPIC) schemes which achieve significantly increased compression (approaching 35:1) with improved fidelity and the very low complexity associated with VPIC are described. HVPIC employs standard VPIC embedded in a multiresolution (pyramid) structure. Low-resolution images coded at the upper levels augment coding of the higher-resolution images. Interactions between resolution levels is simple and efficient, yielding little increase in complexity relative to VPIC.< >
We describe a system that performs model‐based recognition of the projections of generalized cylinders, and present new results on the final classification of the feature data. Two classification methods are proposed...
A particular form of parallelism, called bit-parallelism, is introduced. A bit-parallel organization distributes each bit of a data item to a different processor. Bit-parallelism allows computation that is sublinear w...
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A particular form of parallelism, called bit-parallelism, is introduced. A bit-parallel organization distributes each bit of a data item to a different processor. Bit-parallelism allows computation that is sublinear with word size for such operations as integer addition, arithmetic shifts, and data moves. The implications of bit-parallelism for system architecture are analyzed. An implementation of a bit-parallel architecture based on a mesh with a bypass network is presented. Using a conservative estimate for cycle time, a Silt processor performs 64-b integer additions more than 10 times faster than the Connection Machine-2. Using current CMOS technology, a 16 M processor Silt system would be capable of nearly 500 billion 32-b adds per second. The application of the architecture to low-level vision algorithms is discussed.< >
Relaxation labeling uses contextual information for finding consistent labelings of graphs. Although relaxation labeling is parallel and iterative, the complexity of updating with standard rules is too costly for prac...
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Relaxation labeling uses contextual information for finding consistent labelings of graphs. Although relaxation labeling is parallel and iterative, the complexity of updating with standard rules is too costly for practical implementation. A description is given of a computationally more efficient updating rule that utilizes radial projection instead of normal projection to avoid the complexities incurred by previous update rules when boundaries to the labeling space are encountered. This reduction in complexity is achieved by first restricting support vectors to the positive quadrant, and then using radial projection onto the constraint instead of normal projection. Crucial order information is conserved through smooth convergence towards the optimum and a rate of convergence proportional to the magnitudes of the support functions.
An analysis is presented of the behavior of edges in scale space for deriving rules useful in reasoning. This analysis of liner edges at different scales in images includes the mutual influence of edges and identifies...
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An analysis is presented of the behavior of edges in scale space for deriving rules useful in reasoning. This analysis of liner edges at different scales in images includes the mutual influence of edges and identifies at what scale neighboring edges start influencing the response of a Laplacian or Gaussian operator. Dislocation of edges, false edges, and merging of edges in the scale space are examined to formulate rules for reasoning in the scale space. The theorems, corollaries, and assertions presented can be used to recover edges, and related features, in complex images. The results reported include one lemma, three theorems, a number of corollaries and six assertions. The rigorous mathematical proofs for the theorems and corollaries are presented. These theorems and corollaries are further applied to more general situations, and the results are summarized in six assertions. A qualitative description as well as some experimental results are presented for each assertion.
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