9 January 1984 Synthesis And Applications Of Effective Decision Algorithms For Digital Image Processing On A Basis Of Statistical Invariant Coupling Method
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Abstract
Some problems of digital image processing are considered in the paper. Main attention is paid to effective statistical processing of observations obtained thereby. Statistical invariant coupling method which is the basis for constructing synthesis of effective decision algorithms is used for the purpose. Optimum sampling procedures are also discussed. The results are presented as components of the single algorithm for determining homo-geneous regions boundaries in the composite picture which provides determination of the closed boundaries. The image to be analysed is first broken into equal segments after which statistically similar segments are merged into homogeneous regions corresponding to the objects in the picture. Decision whether it is possible or not to add to the region the next segment is found by checking statistical hypotheses. Formation of the region is terminated when no segment can be added to it any more. The process of differentiation of homogeneous regions follows next. Questions of optimum forming standard observations samples for differentiation of regions are also outlined. The algorithm in question may be used, for instance, for classification of aerial photographs of t he Earth surface, for natural resources examination, classification of surface for aerial survey for laying routes in the sea under conditions of winter ship navigation. It can essentially solve the following problems: terrain classification, effective coding and decoding of information, selection of most informative properties, etc. A number of new results have been obtained. The paper cites examples for illustrative purposes.
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Nicolai A. Nechval, "Synthesis And Applications Of Effective Decision Algorithms For Digital Image Processing On A Basis Of Statistical Invariant Coupling Method", Proc. SPIE 0432, Applications of Digital Image Processing VI, (9 January 1984); doi: 10.1117/12.936637; https://doi.org/10.1117/12.936637
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