"Wavelet De-noising in Image Segmentation"@en . "9"^^ . "978-80-7395-077-4" . "RIV/60461373:22340/08:00020895!RIV09-MSM-22340___" . . "Wavelet De-noising in Image Segmentation"@en . "Proceedings the 8th International Scientific - Technological Conference Process Control 2008" . . . "Segmentace obraz\u016F s potla\u010Den\u00FDmi ru\u0161iv\u00FDmi slo\u017Ekami pomoc\u00ED jejich wavelet dekompozice"@cs . "1"^^ . "Proch\u00E1zka, Ale\u0161" . . "RIV/60461373:22340/08:00020895" . "Univerzita Pardubice" . . "22340" . . "405564" . "P\u0159\u00EDsp\u011Bvek je v\u011Bnov\u00E1n segmentaci obraz\u016F a robustnosti d\u00EDl\u010D\u00EDch motod s ohledem na \u00FArove\u0148 potla\u010Den\u00ED \u0161umu s pou\u017Eit\u00EDm prahov\u00E1n\u00ED wavelet koeficient\u016F. Navr\u017Een\u00E9 metody jsou ov\u011B\u0159ov\u00E1ny na re\u00E1ln\u00FDch datech a pro re\u00E1ln\u00E9 MR obrazy s r\u016Fznou strukturou. P\u0159\u00EDsp\u011Bvek zmi\u0148uje rovn\u011B\u010D citlivost v\u016F\u010Di osv\u011Btlen\u00ED, m\u011B\u0159\u00EDtku, rotaci a posunu."@cs . . "2"^^ . . "Wavelet De-noising in Image Segmentation" . . "Wavelet De-noising in Image Segmentation" . "2008-06-09+02:00"^^ . . . "Gavlasov\u00E1, Andrea" . "Segmentace obraz\u016F s potla\u010Den\u00FDmi ru\u0161iv\u00FDmi slo\u017Ekami pomoc\u00ED jejich wavelet dekompozice"@cs . "[A1AB65DBFA39]" . "Pardubice" . . "The paper is devoted to the image segmentation using different methods and to comparison of their robustness with respect to various levels of noise. Proposed de-noising procedures are based upon appropriate thresholding of wavelet transform coefficients evaluated by selected decomposition functions. Resulting methods are verified for simulated images and then applied for selected MR biomedical images containing different structures. Sensitivity of segmentation to image components illumination, scale, translation and rotation is mentioned as well." . "discrete wavelet transform; thresholding; image segmentation"@en . . "Z(MSM6046137306)" . . . "The paper is devoted to the image segmentation using different methods and to comparison of their robustness with respect to various levels of noise. Proposed de-noising procedures are based upon appropriate thresholding of wavelet transform coefficients evaluated by selected decomposition functions. Resulting methods are verified for simulated images and then applied for selected MR biomedical images containing different structures. Sensitivity of segmentation to image components illumination, scale, translation and rotation is mentioned as well."@en . . "Kouty nad Desnou" .