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Application of Wavelet Theory in Image Diffusion

Author: CaiHaoJiang
Tutor: FengXiangChu
School: Xi'an University of Electronic Science and Technology
Course: Computational Mathematics
Keywords: Wavelet Partial Differential Equations Denoising Threshold Convective term
CLC: TP391.41
Type: Master's thesis
Year: 2009
Downloads: 83
Quote: 1
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In recent years , partial differential equations for image processing and wavelet method is not only on the theoretical study a new subject , and also played an important role in promoting the development of image processing , it is both important theoretical value , and there are broad prospects for development . Denoising is one of its important applications . This article describes the history of the development of image processing , a mathematical model of the basic knowledge of digital image image image processing effect evaluation method focuses on the application of partial differential equations and wavelet analysis in image processing . Multiresolution analysis and wavelet transform, and then given Mallat tower algorithm , to discuss the application of wavelet transform denoising . Discussed several classical equations of partial differential equations in image processing applications : heat diffusion equation , Perona-Malik model Weickert anisotropic diffusion model , and thus the the Weickert model is proposed improved . Partial differential equations used to process the image , the the image repeated iterations of this process is the whole image , to be able to save the image edge , but the fuzzy image texture ; wavelet transform is able to focus the image subtle changes , but there will be a dumbbell effect . The organic combination of the two will overcome the shortcomings of their own , to obtain better results . Good order during image processing , noise suppression , and as much as possible to keep the image details , this paper presents a wavelet transform and nonlinear diffusion bonding image processing method , the method of wavelet transform time-frequency localization edge enhancement characteristics and nonlinear diffusion of image processing . Finally, through the simulation experiment to verify this Denoising more before denoising algorithm , the image quality has improved to some extent .

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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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