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As an important kind of aggregation function, overlap functions are widely used in information fusion, data intelligence, image processing, decision science, etc. It is also used to construct new fuzzy rough set models. Moreover, fuzzy rough sets have been deeply studied and made great progress in data analysis and mining, feature selection, and other fields. However, after studying a large amount of literature, we find that the current research includes the following issues. First, existing fuzzy rough set models based on overlap functions (O-FRSs) need to be optimized (for example, the definition of fuzzy rough lower approximation in ( I_O , O )-fuzzy rough sets is not flexible, which restricts the application of ( I_O , O )-fuzzy rough sets). Second, the application research of O-FRSs is rarely involved, and the advantages of O-FRSs in feature selection and image processing are not presented. In this article, combining the …