In order to rapidly and accurately detect infrared small and dim targets in the infrared image of complex scene collected by virtual prototyping of space-based downward-looking multiband detection,an improved detectio...In order to rapidly and accurately detect infrared small and dim targets in the infrared image of complex scene collected by virtual prototyping of space-based downward-looking multiband detection,an improved detection algorithm of infrared small and dim target is proposed in this paper.Firstly,the original infrared images are changed into a new infrared patch tensor mode through data reconstruction.Then,the infrared small and dim target detection problems are converted to low-rank tensor recovery problems based on tensor nuclear norm in accordance with patch tensor characteristics,and inverse variance weighted entropy is defined for self-adaptive adjustment of sparseness.Finally,the low-rank tensor recovery problem with noise is solved by alternating the direction method to obtain the sparse target image,and the final small target is worked out by a simple partitioning algorithm.The test results in various spacebased downward-looking complex scenes show that such method can restrain complex background well by virtue of rapid arithmetic speed with high detection probability and low false alarm rate.It is a kind of infrared small and dim target detection method with good performance.展开更多
This paper presents a novel consensus clustering(CC)approach for a document repository concerning power substations(PSD)and contributes to the intangible asset management of power systems.A domain ontology model,i.e.,...This paper presents a novel consensus clustering(CC)approach for a document repository concerning power substations(PSD)and contributes to the intangible asset management of power systems.A domain ontology model,i.e.,substation ontology(SONT),is applied to modify the traditional vector space model(VSM)for document representation,which is concerned with the semantic relationship between terms.A new document representation is generated using a term mutual information matrix with the aid of SONT.In addition,compared with two other novel CC algorithms,i.e.,non-negative matrix factorisation-based CC(NNMF-CC)and information theory-based CC(INT-CC),weighted partition via kernel-based CC algorithm(WPK-CC)is utilised to solve the CC issue for PSD.Meanwhile,genetic algorithms(GA)were applied to WPK-CC for PSD,as there are limitations in the original WPK-CC for document clustering.Subsequently,selected mechanisms in each GA’s procedure are compared and improved,resulting in comprehensive parameter settings for the PSD CC.Four simulation studies have been designed,in which the results are evaluated by purity validation method and show that the SONT-based document representation and improved WPK-CC,via modified GA,significantly improve the performance of the PSD CC.展开更多
文摘In order to rapidly and accurately detect infrared small and dim targets in the infrared image of complex scene collected by virtual prototyping of space-based downward-looking multiband detection,an improved detection algorithm of infrared small and dim target is proposed in this paper.Firstly,the original infrared images are changed into a new infrared patch tensor mode through data reconstruction.Then,the infrared small and dim target detection problems are converted to low-rank tensor recovery problems based on tensor nuclear norm in accordance with patch tensor characteristics,and inverse variance weighted entropy is defined for self-adaptive adjustment of sparseness.Finally,the low-rank tensor recovery problem with noise is solved by alternating the direction method to obtain the sparse target image,and the final small target is worked out by a simple partitioning algorithm.The test results in various spacebased downward-looking complex scenes show that such method can restrain complex background well by virtue of rapid arithmetic speed with high detection probability and low false alarm rate.It is a kind of infrared small and dim target detection method with good performance.
基金supported by the National Natural Science Foundation of China(No.51477054)Guangdong Innovative Research Team Program(No.201001N0104744201).
文摘This paper presents a novel consensus clustering(CC)approach for a document repository concerning power substations(PSD)and contributes to the intangible asset management of power systems.A domain ontology model,i.e.,substation ontology(SONT),is applied to modify the traditional vector space model(VSM)for document representation,which is concerned with the semantic relationship between terms.A new document representation is generated using a term mutual information matrix with the aid of SONT.In addition,compared with two other novel CC algorithms,i.e.,non-negative matrix factorisation-based CC(NNMF-CC)and information theory-based CC(INT-CC),weighted partition via kernel-based CC algorithm(WPK-CC)is utilised to solve the CC issue for PSD.Meanwhile,genetic algorithms(GA)were applied to WPK-CC for PSD,as there are limitations in the original WPK-CC for document clustering.Subsequently,selected mechanisms in each GA’s procedure are compared and improved,resulting in comprehensive parameter settings for the PSD CC.Four simulation studies have been designed,in which the results are evaluated by purity validation method and show that the SONT-based document representation and improved WPK-CC,via modified GA,significantly improve the performance of the PSD CC.
