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Image Decomposition Algorithm with a Structural Constraint of the Averaging Region

  • MATHEMATICAL THEORY OF IMAGES AND SIGNALS REPRESENTING, PROCESSING, ANALYSIS, RECOGNITION, AND UNDERSTANDING
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Abstract

Decomposition, i.e., partitioning an image into components with different information content, is used to solve many problems of processing and analyzing of video information. The separation of an image into piecewise smooth structural and texture-noise components is of interest. The problem is the preservation of the signal structure, since independent smoothing is required in each of the image areas that reflect a particular object in the scene. Most of the known smoothing-used decomposition methods are based on the indirect characteristics of the local area of the image, for example, the distribution of signal values, which does not reflect its structural features sufficiently well. The criterion for limiting the smoothing area should be the fact that the target and surrounding points belong to the same spatial area of the image. A sufficient condition for the connectivity of the points of the region is the absence of contour lines between them. An approach to decomposition based on the preliminary delineation of the image areas by detecting contour (brightness) differences between them and subsequent contour-constrained smoothing inside each of the areas is proposed. The concept of the affinity of points in the image is introduced, based on which the smoothing algorithm is built. Experimental comparisons of the proposed algorithm with other well-known image smoothing algorithms are carried out.

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Correspondence to P. A. Chochia.

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This article is a completely original study by the author; it has not been previously published, and will not be published in other publications.

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Pavel Antonovich Chochia, born 1951. Graduated from Moscow Institute of Physics and Technology in 1974. Defended his Candidate’s dissertation in 1982 and his Doctoral dissertation in Technical Sciences in 2016. Senior Researcher and Associate Professor at the Institute for Information Transmission Problems (Kharkevich institute), Russian Academy of Sciences (IITP RAS). Scientific Interests: mathematical models of images, methods of image decomposition and smoothing, issues of assessing the complexity of an image, methods of processing and analyzing video information, detection of objects in an image, multidimensional variations, image segmentation, specialized operating systems for image processing, etc. Author of more than 120 papers, including three patents and one book. Member of the editorial board of the journal Information Processes. Member of Dissertation Council D 002.077.05 of the IITP RAS. Awards: two bronze medals of the USSR Exhibition of Economic Achievements for processing images transmitted by interplanetary spacecraft. Nominee for the Grand Prix “Golden Softies” in Europe (CeBit exhibition, Hannover, 1992).

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Chochia, P.A. Image Decomposition Algorithm with a Structural Constraint of the Averaging Region. Pattern Recognit. Image Anal. 31, 394–401 (2021). https://doi.org/10.1134/S1054661821030056

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  • DOI: https://doi.org/10.1134/S1054661821030056

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