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Please use this identifier to cite or link to this item: http://192.168.1.231:8080/dulieusoDIGITAL_123456789/6111
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dc.contributor.authorNguyễn Vĩnh An-
dc.date.accessioned2020-06-25T22:31:14Z-
dc.date.available2020-06-25T22:31:14Z-
dc.date.issued2020-
dc.identifier.urihttp://192.168.1.231:8080/dulieusoDIGITAL_123456789/6111-
dc.description.abstractmage denoising is aimed at the removal of noise which may corrupt an image during its acquisition or transmission. De-noising of the corrupted image by Gaussian noise using wavelet transform is very effective way because of its ability to capture the energy of a signal in few larger values. This paper proposes a threshold selection method for image de-noising based on the statistical parameters which depended on sub-band data. The threshold value is computed based on the number of coefficients in each scale jof wavelet decomposition and the noise variance in various sub-band. Experimental results in PSNR on several test images are compared for different de-noise techniquesen_US
dc.publisherĐại học Quốc gia Hà Nộien_US
dc.titleAnalysis the Statistical Parameters of the Wavelet Coefficients for Image Denoisingen_US
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