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Title: WAVELET SIGNAL AND IMAGE DENOISING
Page Link: WAVELET SIGNAL AND IMAGE DENOISING -
Posted By: seminar class
Created at: Tuesday 03rd of May 2011 05:32:00 PM
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Abstract
The paper deals with the use of wavelet transform for signal and image de-noising
employing a selected method of thresholding of appropriate decomposition coef-
¯cients. The proposed technique is based upon the analysis of wavelet transform
and it includes description of global modi¯cation of its values. The whole method
is veri¯ed for simulated signals and applied to processing of biomedical signals
representing EEG signals and MR images corrupted by additional random noise.
1 Introduction
The wavelet transfo ....etc

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Title: matlab code for image denoising using adaptive wavelet thresholding
Page Link: matlab code for image denoising using adaptive wavelet thresholding -
Posted By:
Created at: Friday 11th of January 2013 05:24:19 PM
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Hi,
Could you please show me how to implement the adaptive wavelet thresholding for denoising in MATLAB.
Thank you verymuch. ....etc

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Title: curvelet transform for image denoising
Page Link: curvelet transform for image denoising -
Posted By: vidhya chandran
Created at: Wednesday 10th of November 2010 08:05:24 PM
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Title: bilateral filter image denoising
Page Link: bilateral filter image denoising -
Posted By: zaheer_99
Created at: Monday 01st of August 2011 03:54:56 AM
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hi everybody, can anybody help me about bilateral filter image denoising, i need any project report or thesis about my topic, thanks alot. you can contact me on my mail address([email protected]). ....etc

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Title: SIMULTANEOUS FRACTAL IMAGE DENOISING AND INTERPOLATION
Page Link: SIMULTANEOUS FRACTAL IMAGE DENOISING AND INTERPOLATION -
Posted By: project report helper
Created at: Thursday 07th of October 2010 05:46:17 PM
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SIMULTANEOUS FRACTAL IMAGE DENOISING AND INTERPOLATION


M. Ghazel R. K. Ward R. Abugharbieh

University of British Columbia
ECE Dept.
Vancouver, B.C. V6T 1Z

E. R. Vrscay , G. H. Freeman
University of Waterloo
Applied Math Dept ECE Dept
Waterloo, ON. N2L 3G1

ABSTRACT

In this paper, a simple and effective fractal-based simultaneous image denoising and interpolation scheme is proposed and implemented. The denoising is performed during the fractal encoding process while the interpolation is perfor ....etc

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Title: image denoising simulink model
Page Link: image denoising simulink model -
Posted By:
Created at: Sunday 04th of November 2012 12:24:17 AM
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Title: image denoising using curvelet transform ppt
Page Link: image denoising using curvelet transform ppt -
Posted By:
Created at: Wednesday 10th of October 2012 10:57:30 AM
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Title: The Curvelet Transform For Image Denoising
Page Link: The Curvelet Transform For Image Denoising -
Posted By: seminar addict
Created at: Saturday 21st of January 2012 04:46:22 PM
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The Curvelet Transform For Image Denoising


Image denoising using Wavelet

Over the last decade, there has been abundant interest in wavelet methods for noise removal in signals and images.

Initial efforts included very simple ideas like thresholding of the orthogonal wavelet coefficients of the noisy data, followed by reconstruction


The new Transforms


The new ridgelet and curvelet transforms were developed over several years in an attempt ....etc

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Title: matlab code for image denoising using fuzzy logic
Page Link: matlab code for image denoising using fuzzy logic -
Posted By:
Created at: Wednesday 23rd of January 2013 08:38:27 PM
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i am in need of matlab code for image denoising using fuzzy logic ....etc

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Title: Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering
Page Link: Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering -
Posted By: seminar surveyer
Created at: Friday 08th of October 2010 02:45:22 PM
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Abstract

We propose a novel image denoising strategy based on an enhanced sparse representation in transform domain. The enhancement of the sparsity is achieved by grouping similar 2-D image fragments (e.g., blocks) into 3-D data arrays which we call “groups.” Collaborative filtering is a special procedure developed to deal with these 3-D groups. We realize it using the three successive steps: 3-D transformation of a group, shrinkage of the transform spectrum, and inverse 3-D transformation. The result is a 3-D estima ....etc

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