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Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/8671

Title: Image denoising based on dual-tree complex discrete wavelet transform
Authors: Hadeel Nasrat, Abdullah
Shaikh N. S., AB Rahman
A. N., Abdalla
Keywords: Denoising;Dual tree;Complex wavelet transform;Malaysian Technical Universities Conference on Engineering and Technology (MUCEET)
Issue Date: 20-Jun-2009
Publisher: Universiti Malaysia Pahang (UMP)
Citation: p.1-3
Series/Report no.: Proceedings of the Malaysian Technical Universities Conference on Engineering and Technology (MUCEET) 2009
Abstract: Complex discrete wavelet transform (CDWT) has significant advantages over real wavelet transform for certain signal processing problems. In this paper, denoising of SAR images based on Complex discrete wavelet transform (CDWT) was proposed. The dual-tree CDWT uses length-10 filters to obtain their real and imaginary parts. The top-level denoising strategy same as most other wavelet based denoising algorithms; decompose the noisy image into L levels of 6 directional subbands and a set of (lowpass) scaling coefficients, denoise the complex wavelet coefficients in each subband except for the scaling coefficients and invert the transform to obtain the image estimate. Experiment result shows a great effectiveness of Dual-Tree CDWT in removing the noise compared to the classical DWT.
Description: MUCEET 2009 is organized by Malaysian Technical Universities Network (MTUN) comprising of Universiti Malaysia Perlis (UniMAP), Universiti Tun Hussein Onn (UTHM), Universiti Teknikal Melaka (UTeM) and Universiti Malaysia Pahang (UMP), 20th - 22nd June 2009 at M. S. Garden Hotel, Kuantan, Pahang.
URI: http://hdl.handle.net/123456789/8671
Appears in Collections:Conference Papers

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