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Research of Image Denoising Based on the Multi-wavelet

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Tutor: ZhouJiaJi
School: Chengdu University of Technology
Course: Applied Computer Technology
Keywords: Denoising,Multiwavelet,Coefficient of correlation,Wiener filter
CLC: TP391.41
Type: Master's thesis
Year:  2010
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Abstract:
Image capture and transfer process, often by a variety of factors, interference, so it is necessary to study image denoising. Denoising is the content of the image processing is an important research. In recent years, developed wavelet based on multiwavelet orthogonality, symmetry, smoothness, compact support features at the same time, get the people's attention, including image processing and other fields has been widely used in signal. The image denoising There are many, but the use of multi-wavelet image denoising is a just beginning to get concerned about the research topic, both in theory and in practice has great significance. Image denoising method based on wavelet transform is a more in-depth studies, including: a detailed study of a wavelet and multi-wavelet theory;, traditional denoising method, in particular based on wavelet thresholding shrinkage denoising based multiwavelet multilevel threshold shrink denoising method detailed study and analysis of the more common based on wavelet multiwavelet denoising algorithm threshold. Shrinkage denoising method inadequate for wavelet thresholding, a detailed analysis of the improved algorithm based on wavelet Wiener filtering, the method still has the wavelet coefficients in the local and additive Gaussian noise is still subject to different scales and in different directions Gaussian distribution, only the characteristics of the noise of different sizes Wiener filtering. Wiener filtering method based on wavelet multiwavelet basis to improve the use of the wavelet coefficients and noise distribution characteristics of image wavelet transform coefficient is still wavelet coefficient decomposition finer noise variance estimate more accurately the characteristics of the image multi-wavelet transform coefficient of the Wiener filter denoising method using Matlab software, the simulation test, test and verify the effectiveness of the method. The paper analyzes the multiwavelet denoising theory and image preprocessing, the multiwavelet transform key technologies, its advantages theoretically GHM multiwavelets denoising and experimental use of process steps do introduced, and other commonly used wavelet CL wavelet, SA4 wavelet, etc., and laid the foundation for future work. The Wiener filter is an adaptive filtering, Gaussian noise particularly good denoising effect. It can be based on the region variance to adjust the output of the filter, the larger the subregion variance, the stronger the smoothing effect. The paper presents the image wavelet transform coefficients in the Wiener filter denoising method, which achieved a good image denoising effect.
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