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Image Denoising Based on Partial Differential Equations

Author: XingYueQi
Tutor: WangWeiWei
School: Xi'an University of Electronic Science and Technology
Course: Computational Mathematics
Keywords: Partial Differential Equations Denoising Hops law The impact of filtering
CLC: TP391.41
Type: Master's thesis
Year: 2009
Downloads: 253
Quote: 3
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Abstract


With the continuous development of computer technology , image processing has been more and more attention and study . Currently, image processing method has the following three categories: probability and statistics - based approach based on Fourier and wavelet transform method based on the method of partial differential equations . PDE image processing method due to its strong adaptive , anisotropic diffusion characteristics in processing the image at the same time can be very good to keep the edge and texture details , in the past 25 years the huge development . Image denoising based on partial differential equations , the following study : the solution of nonlinear diffusion partial differential equations , finite difference scheme for the introduction of hops . Explicit finite difference scheme for solving nonlinear diffusion equation is generally , but significantly format in order to ensure its stability , the time step restrictions more stringent jump point finite difference scheme is explicit , implicit binding and is unconditionally stable , so You can select larger time step , thus speeding up the processing of the images . Based on the analysis of the impact of filtering and nonlinear diffusion equations based on the model of the impact filtering coupled diffusion equation , and that part of the increase in the impact of filtering an anisotropic diffusion , and to the diffusion term plus the weighting function , image smoothing and edge sharpening and achieved good results.

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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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