21 July 2017 New grayscale morphological operators on hypergraph
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Proceedings Volume 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017); 1042023 (2017) https://doi.org/10.1117/12.2281660
Event: Ninth International Conference on Digital Image Processing (ICDIP 2017), 2017, Hong Kong, China
Abstract
New grayscale morphological operators on hypergraph are proposed to avoid the loss of details caused by fixed structure element effectively. Hypergraph, the most general structure in discrete mathematics, is also a subset of a finite set. Being a structured representation of information, the ordinary image can be transformed into a hypergraph model, which can integrate hypergraph theory with mathematical morphology theory. Because hypergraphs have good performance in structuring information, first of all, this paper designs a reasonable method of turning grayscale images into hypergraph space. Then based on hypergraph theory, new grayscale morphological operators on hypergraph are defined. Experiments show that using the new operators can avoid the loss of image detail information, and improve the precision of image processing.
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Junping Wang, Junping Wang, Gangming Liang, Gangming Liang, Yahui Zheng, Yahui Zheng, Yao Wu, Yao Wu, } "New grayscale morphological operators on hypergraph", Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 1042023 (21 July 2017); doi: 10.1117/12.2281660; https://doi.org/10.1117/12.2281660
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