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Image Processing Based on Partial Differential Equations

Author: WangHongYou
Tutor: WangWeiWei
School: Xi'an University of Electronic Science and Technology
Course: Computational Mathematics
Keywords: Nonlinear structure tensor Edge Enhancement Denoising Non - local operator
CLC: TP391.41
Type: Master's thesis
Year: 2009
Downloads: 349
Quote: 3
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Abstract


In the past two decades , with the development of computer technology , image processing has been more and more attention and study . The Image Denoising is an important part of the image processing , has important implications for improving image quality . In recent years , based on partial differential equations (Partial Differential Equation, abbreviation PDE) image processing by the attention . Compared to other methods , partial differential equations has the following advantages : first , strong local self-adaptive ( Local adaptability ) ; Second, the formal normative (unification); Third, a high degree of flexibility (flexibility) . Partial differential equations in denoising better able to maintain the edge , texture , and other details . The development of the theory of partial differential equations (PDE) experienced from linear to nonlinear isotropic diffusion to anisotropic diffusion process . Anisotropic diffusion equation is a nonlinear partial differential equation model . This paper mainly discussed on the basis of partial differential equation models elaborated image denoising model based on nonlinear structure tensor image edge enhancement , and equation parameters discussed . Experimental results show that , based on nonlinear structure tensor image edge enhancement model can effectively improve the quality of the image . Using the concept of non- local derivative ROF model to promote the local non - local anisotropic diffusion .

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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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