中南大学学报（自然科学版）2013，Vol.44Issue(1)：166-171,6.
基于上下文模型的混合傅里叶-小波图像降噪方法
Fourier-wavelet image reduction using context-based model
摘要
Abstract
The strengths and weaknesses of Fourier transform and wavelet transform were discussed in the process of image-denoising. The image noise reduction methods were proposed using Fourier-wavelet transforms context-based model. The original image noise level was reduced by estimation of power spectral density of the original image in the Fourier domain and the use of Wiener filter. The remaining noise was removed by using adaptive wavelet threshold method based on context modeling. A series of wavelet coefficients were obtained by using the stationary wavelet transform to decompose the image signal. According to the correlation among those coefficients, the variance of wavelet coefficients was calculated by using the context model. The adaptive threshold was acquired by substituting the variance into the threshold expression estimated by the GGD model. Processing wavelet coefficients with soft thresholding function, the image denoise was completed by means of the wavelet inverse transform to wavelet coefficients. Simulation results show that the methods proposed can not only effectively filter out image noise, but also keep the edges of the image detail signal well and inhibit Gibbs phenomenon caused by noise reduction.关键词
上下文模型/傅里叶-小波变换/图像去噪Key words
context model/ Fourier-wavelet transform/ image denoising分类
信息技术与安全科学引用本文复制引用
邓宏贵,李明辉,高小龙..基于上下文模型的混合傅里叶-小波图像降噪方法[J].中南大学学报（自然科学版）,2013,44(1):166-171,6.基金项目
国家自然科学基金资助项目(61071025) （61071025）
中南大学学位论文创新基金资助项目(2010ssxt012) （2010ssxt012）
