A simple image smoothing scheme for improving the quality of noisy pictures is proposed. This scheme employs a 3 by 3 mask in which the weighting coefficients re the normalized gradient inverses. The smoothing operati...
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A simple image smoothing scheme for improving the quality of noisy pictures is proposed. This scheme employs a 3 by 3 mask in which the weighting coefficients re the normalized gradient inverses. The smoothing operation will clean out noises inside a region without blurring its boundary. Simulation studies show that this method tends to reduce the gray level variance within a region, and keep its mean relatively unchanged. Results of applications to several real world images are presented.
It is shown that the Hough transform may be used for encoding of line curves and waveforms that consist of the concatenation of curves from an underlying set of families of curves. Several properties of the transform ...
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It is shown that the Hough transform may be used for encoding of line curves and waveforms that consist of the concatenation of curves from an underlying set of families of curves. Several properties of the transform are given in this context.
A map-guided approach to interpretation of remotely sensed imagery is described, with emphasis on applications involving continuous monitoring of predetermined ground sites. Geometric correspondence between a sensed i...
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A map-guided approach to interpretation of remotely sensed imagery is described, with emphasis on applications involving continuous monitoring of predetermined ground sites. Geometric correspondence between a sensed image and a symbolic reference map is established in an initial stage of processing by adjusting parameters of a sensor model so that image features predicted from the map optimally match corresponding features extracted from the sensed image. Information in the map is then used to constrain where to look in an image and what to look for. With such constraints, previously intractable remote sensing tasks can become feasible, even easy, to automate.
A picture digitization grid based on logarithmic spirals rather than Cartesian coordinates is presented. Expressing this curvilinear grid as a conformal exponential mapping reveals useful imageprocessing properties. ...
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A picture digitization grid based on logarithmic spirals rather than Cartesian coordinates is presented. Expressing this curvilinear grid as a conformal exponential mapping reveals useful imageprocessing properties. The mapping induces a computational simplification that suggests parallel architectures in which most geometric transformations are effected by data shifting in memory rather than arithmetic on coordinates. These include fast, parallel noise-free rotation, scaling, and some projective transformations of pixel defined images. conformality of the mapping preserves local picture-processing operations such as edge detection.
Shape description and recognition is an important and interesting problem in scene analysis. The authors approach to shape description is a formal model of a shape consisting of a set of primitives, their properties, ...
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Shape description and recognition is an important and interesting problem in scene analysis. The authors approach to shape description is a formal model of a shape consisting of a set of primitives, their properties, and their interrelationships. The primitives are the simple parts and intrusions of the shape which can be derived through the graph-theoretic clustering procedure previously described. The interrelationships are two ternary relations on the primitives: the intrusion relation which relates two simple parts that join to the intrusion they surround and the protrusion relation which relates two intrusions to the protrusion between them. Using this model, a shape matching procedure that uses a tree search with look-ahead to find mappings from a prototype shape to a candidate shape has been developed.
The k-syntactic similarity approach is couched in graphical representation terms and its ability to provide global recognition capability while retaining a low time complexity is explored. One potential application do...
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The k-syntactic similarity approach is couched in graphical representation terms and its ability to provide global recognition capability while retaining a low time complexity is explored. One potential application domain, that of composite shape decomposition into approximately convex subshapes, is described. This is shown to be equivalent to finding cycles within a particular graph. The approach yields valid decompositions in many cases where additional semantic considerations are necessary for proper analysis. The permissible graph structures representing composite shapes given a reasonable set of relations are determined. Experimental results on non-ideal data are given.
Large images are becoming more and more common in earth resources monitoring, medical diagnosis and other applications. Often it would be helpful to work with only a subset of a large image since less space and time w...
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Large images are becoming more and more common in earth resources monitoring, medical diagnosis and other applications. Often it would be helpful to work with only a subset of a large image since less space and time would be required to process it. Subsets extracted according to semantic attributes have irregular shapes and as such are awkward to store and process. Irregular subsets can be covered with rectangular regions to simplify the regions to be stored and processed. Then the rectangular regions must be organized with an index. Here several covering methods are compared and indexing methods suggested. A surprizing result is that the sequential-greatest coverage heuristic can lead to arbitrarily bad coverings in some situations. However, this disadvantage can be overcome by combination with a tiling approach.
The problem of estimating the error probability of a given classification system is considered. Statistical properties of the empirical error count (C) and the average conditional error (R) estimators are studied. It ...
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The problem of estimating the error probability of a given classification system is considered. Statistical properties of the empirical error count (C) and the average conditional error (R) estimators are studied. It is shown that in the large sample case the R estimator is unbiased and its variance is less than that of the C estimator. In contrast to conventional methods of Bayes error estimation the unbiasedness of the R estimator for a given classifier can be obtained only at the price of an additional set of classified samples. On small test sets the R estimator may be subject to a pessimistic bias caused by the averaging phenomenon characterising the functioning of conditional error estimators.
The growing use and analysis of images by computer presents many problems in managing images and image information. Solutions to these problems can be specific, with file structures to represent the needed information...
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The growing use and analysis of images by computer presents many problems in managing images and image information. Solutions to these problems can be specific, with file structures to represent the needed information, or general, such as a general Data Base Management System. A presentation is made of a compromise solution, a Raster image File Format (RIFF), that uses image file headers for the storage of specific image format information, as well as very general Name-Value pair information. This latter structure enables varying kinds of information to be represented, including links to other kinds of image data structures as the need arises.
Quantitative analysis of lung tissue micrographs aims primarily at the determination of three-dimensional properties of the lung from two-dimensional micrographs. A computer-based approach to the determination of lung...
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Quantitative analysis of lung tissue micrographs aims primarily at the determination of three-dimensional properties of the lung from two-dimensional micrographs. A computer-based approach to the determination of lung tissue boundaries and triple points and end points from the micrograph is presented. The lung tissue boundaries are determined by histogram enhancement approach and zoom thresholding technique. The binary picture representing the lung tissue is then undergoing a thinning process to generate its skeleton from which the triple points and end points are automatically determined. The processing algorithms are developed into a software package implemented on a PDP-11/40 minicomputer.
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