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- W2377322891 abstract "In order to remove the millimeter wave image noise effectively and improve the accuracy of target identification,a novel image de-noising method based on BEMD(Bi-dimensional Empirical Mode Decomposition) and Dual-tree Complex Wavelet Transform(DTCWT) integrated with Wiener filter is proposed.Firstly,BEMD was carried out to decompose the millimeter wave image including noise into a group of Intrinsic Mode Functions(IMF) sub images with different intrinsic time scales.Secondly,the first several IMF sub images corresponding to high frequency information and noise were decomposed with different scales and directions by means of dual-tree complex wavelet transform,and then the Wiener filter with elliptic direction windows was used to de-noise each high-frequency direction sub-band.Finally,the image was reconstructed through adding the processed IMF and the residual component.Simulation results show that,compared with the single BEMD,DTCWT-Wiener filter and discrete wavelet transform-Wiener filter,this proposed method can not only have advantages of more sufficiently retaining edge and detail information while de-noising,but also achieve superior PSNR(peak signal-noise-ratio) of the reconstructed image." @default.
- W2377322891 created "2016-06-24" @default.
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- W2377322891 date "2011-01-01" @default.
- W2377322891 modified "2023-09-24" @default.
- W2377322891 title "Millimeter wave image de-noising based on BEMD and dual-tree complex wavelet transform integrated with local Wiener filtering" @default.
- W2377322891 hasPublicationYear "2011" @default.
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