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Image Denoising Based on Multiscale Geometric Analysis

Author: WangMei
Tutor: HouZhenJie
School: Inner Mongolia Agricultural University
Course: Applied Computer Technology
Keywords: Multiscale geometric ananlysis Contourlet transform Ridgelet transform Wavelet transform Scale factor Image denoising
CLC: TP391.41
Type: Master's thesis
Year: 2012
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Abstract


The edge and outline of image are very useful in the pattern recognition.But there are much difficulties if the signals are polluted by noise. Ridgelet transform is a new kind of non-adaptive high-dimensional functions after Wavelet transform. For image processing, Ridgelet transform is more effective than the Wavelet transform in representing linear and super-plane singularities.The main work of this dissertation includes:In this paper,we first introduce the theory of Ridgelet transform,and then propose a method for image denoising on scale factor and Ridgelet transform.. In order to indicate its advantages, use Ridgelet to remove noises in images,and compare the results with that of Wavelet. Experiments show that the performance of the proposed method is obviously superior to other methods both in vision and in SNR.In this paper,we first introduce the multiscale geometric analysis theory,and then propose a method for image denoising on scale factor and contourlet transform. Experiments show that the performance of the proposed method is obviously superior to other methods both in vision and in SNR.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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