Pentland (1987) proposed an algorithm for sensing scene depth by measuring the amount of defocus of an image. The algorithm is interesting in the sense that no correspondence problems are involved. The authors discuss...
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(纸本)081861952x
Pentland (1987) proposed an algorithm for sensing scene depth by measuring the amount of defocus of an image. The algorithm is interesting in the sense that no correspondence problems are involved. The authors discuss the difference between shape from defocus and shape from focus and then present a two-phase algorithm where the defocus process is modeled as a two-dimensional Gaussian point-spread function. During the first phase (calibration phase), a camera system parameter is determined off-line. In the next phase (depth-recovery phase), this parameter is used to recover on-line the scene depth by taking two images of the same scene, but with a different amount of defocus. Some implementation issues are addressed, and test results on real images are provided.
An automatic lineament detection technique that is useful in mapping lineaments by imageprocessing Landsat data has been developed. The technique involves the enhancement of linear features, followed by the delineati...
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An automatic lineament detection technique that is useful in mapping lineaments by imageprocessing Landsat data has been developed. The technique involves the enhancement of linear features, followed by the delineation of these enhanced lineaments through patternrecognition techniques. Lineament maps can be produced using this technique, which eliminates subjective decisions and proves very effective in extracting structural and tectonic information.
Summary form only given. The massively parallel processor, or MPP, is a single-instruction-stream, multiple-data-stream (SIMD) computer containing 16,384 bit serial processing elements (PEs) arranged in a 128 × 1...
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Summary form only given. The massively parallel processor, or MPP, is a single-instruction-stream, multiple-data-stream (SIMD) computer containing 16,384 bit serial processing elements (PEs) arranged in a 128 × 128 mesh-connected array. It can be programmed in its assembly language (MCL), MPP Pascal, and MPP Forth. Although the MPP was originally designed primarily for image-processing and pattern-recognition algorithms, can be used effectively in applications in a wide range of general physical and mathematical sciences. image-processing and analysis applications include synthetic aperture radar (SAR) data processing, stereo image analysis for generating topographic maps, sea ice-floe motion detection from time-varying SAR imagery, contextual classification, spatially constrained clustering, neural-network clustering of image data, and image data compression.
A novel formulation for shape-from-shading from multiple images acquired under different viewing and lighting conditions is presented. The method is based on using an explicit image formation model to create rendition...
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A novel formulation for shape-from-shading from multiple images acquired under different viewing and lighting conditions is presented. The method is based on using an explicit image formation model to create renditions of the surface being estimated, which are synthetic versions of the observed images. It is applicable in a variety of imaging situations, including those involving unknown nonuniform albedo. A probabilistic model is developed based on typical characteristics of the surface and minimizing the difference between the synthetic and observed images. This model is used to arrive at Bayesian formulation of the shape-from-shading problem. Techniques are presented to compute an estimate that is statistically optimal in the sense that it is the expected value of the surface, given the set of observations derived from it. The method is applied to Viking imagery of Mars.< >
Traffic observed by video cameras or captured on video tape can now be counted automatically in real-time. The aim of the TRIP II system is to take full advantage of the area sensing capability of video images. It is ...
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Traffic observed by video cameras or captured on video tape can now be counted automatically in real-time. The aim of the TRIP II system is to take full advantage of the area sensing capability of video images. It is different from many earlier systems since it is based upon an inexpensive IBM AT microcomputer and can processes complex pattern information by simulating the operation of a neural network. In this particular case the vehicle detection algorithm relies on the ability of the TRIP II system to learn from example and discriminate between complex patterns within video images of traffic scenes.< >
Presents the vehicle detection algorithms which have been developed using the traffic images collected from various scenes covering 100-250 m of a three three-lanes freeway. Pictures can be of front or rear views. The...
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Presents the vehicle detection algorithms which have been developed using the traffic images collected from various scenes covering 100-250 m of a three three-lanes freeway. Pictures can be of front or rear views. The algorithms cope with the possibility of using remote controlled cameras. This means that the system includes features which are able to re-calibrate the algorithms and to detect the lanes if an operator has moved the camera. Different luminance and traffic conditions are considered. Emphases are made upon the new 'lane detection' module and analysis of dense traffic and nocturnal traffic.< >
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