In this paper, closure operators of lattice-valued propositional logic LP（X） are studied. A family of classical closure operators are defined and the relation between them and closure operators of LP（X） is investi...In this paper, closure operators of lattice-valued propositional logic LP（X） are studied. A family of classical closure operators are defined and the relation between them and closure operators of LP（X） is investigated. At the same time, a tool for checking compactness of LP（X） is given.展开更多
To produce a smoother and more natural interpolated image, and to preserve and enhance original image details, we defined three perception-based local statistic parameters, namely contrast, noise visibility, and edge ...To produce a smoother and more natural interpolated image, and to preserve and enhance original image details, we defined three perception-based local statistic parameters, namely contrast, noise visibility, and edge strength based on three psychophysical principles, including Weber’s Law, Fechner’s Law, and Stevens’ Power Law, and integrated these parameters into a fuzzy logic system to set up an advanced image interpolation algorithm. Application of this algorithm to detect edge behaviors and local statistical information of images demonstrated better noise removal ability and obtained sharper edges than traditional image interpolation algorithems such as nearest neighbor, bilinear and bicubic interpolation methods.展开更多
基金Supported by the National Natural Science Foundation of China(60474022)
文摘In this paper, closure operators of lattice-valued propositional logic LP（X） are studied. A family of classical closure operators are defined and the relation between them and closure operators of LP（X） is investigated. At the same time, a tool for checking compactness of LP（X） is given.
基金Funded by Key Research Project of Liaoning Province Bureau of Science and Technology under the grant No. 2008217004China's Post-Doctoral Science Fund under the grant No. 200704111071
文摘To produce a smoother and more natural interpolated image, and to preserve and enhance original image details, we defined three perception-based local statistic parameters, namely contrast, noise visibility, and edge strength based on three psychophysical principles, including Weber’s Law, Fechner’s Law, and Stevens’ Power Law, and integrated these parameters into a fuzzy logic system to set up an advanced image interpolation algorithm. Application of this algorithm to detect edge behaviors and local statistical information of images demonstrated better noise removal ability and obtained sharper edges than traditional image interpolation algorithems such as nearest neighbor, bilinear and bicubic interpolation methods.
