New grayscale morphological operators on hypergraph

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.