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A Research of Image Denoising and Restoration Based on Total Variation Method

Author: SunYuDan
Tutor: LiuJiCheng
School: Northeast University of Petroleum
Course: Communication and Information System
Keywords: Overall variation Image Denoising Point spread function Image Restoration
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 210
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Abstract


Overall variational method is through the introduction of energy function , the image restoration problem into a functional extremum problem . Is to study the functional extremum problem , this method is widely used in image processing applications. This paper describes the overall variational method based on image denoising and image restoration research . This paper describes the overall variation algorithm based knowledge and the TV image restoration model . In the image denoising part , the paper compares the isotropic diffusion model , TV denoising model, adaptive advantages and disadvantages of TV denoising model , summed up the advantages and disadvantages of the model , and the model change of the regularization parameter , combined with Carl Man filter model for the removal of noise, as proposed a new TV denoising model , the new model while removing the noise , protect the edge information, and reduces the generation of false edge obtain a higher quality image. In the image restoration , first discussed the point spread function of known cases, the use of the overall variation image restoration blurred image restoration model , has been very good experimental results. Subsequently extended to the problem at some unknown point spread function or completely unknown circumstances image restoration problem - blind image restoration problem . During blind image restoration , the paper uses a dual regularization parameter of the overall variation model , the first under the original image and the point spread function and characteristics of some prior knowledge to calculate the estimated value of the point spread function , the blind image restoration problem is transformed become known blur kernel image to ambiguity. Because by the ringing effect , the result is not very satisfactory recovery , but also greatly improves the image quality.

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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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