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- W2360936306 abstract "The existing image fusion method results in uneven image brightness, not agreeing with the original image contrast, not suitable for the human eye visual defects. To solve this problem, a new algorithm based on compressive sensing, which combined the DCT sparse representation with the Dual-channel pulse coupled neural network mode, is offered in this paper. First, for the character of the DCT sparse representation, Radial Sampling Matrix is designed. Second, the measurements based on the weighted average is fused with the information entropy of measurements. Finally, the total variation algorithm is used tore construct the fusion image. Experiments have been done to fuse multiple sets of different types of sensor image. Both subjective visual analysis and objective evaluation criteria show that the proposed algorithm can obtain more useful information from the original image, keep the edge information of original image, and get a better visual effect." @default.
- W2360936306 created "2016-06-24" @default.
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- W2360936306 date "2015-01-01" @default.
- W2360936306 modified "2023-09-25" @default.
- W2360936306 title "An Image Fusion Algorithm Based on DCT Sparse Representation and Dual-PCNN" @default.
- W2360936306 hasPublicationYear "2015" @default.
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