雜訊模式與去雜訊方法

Noise Models and Denoising Techniques

曾怡滿(Yi-Man Tseng)

指導教授 ： 陳宜良

國立臺灣大學/理學院/數學研究所/碩士(2010年)

https://doi.org/10.6342/NTU.2010.01282

摘要

無資料

關鍵字

去雜訊 ； 小波 ； 全變差 ； 軟式閾值 ； 適應性中間值濾波器

並列摘要

We propose to review four common types of image noises, including Gaussian noise, uniform noise, Poisson noise and salt & pepper noise. We set basic one-dimensional and two-dimensional images, and add four types of noises on different levels. We will denoise these corrupted images by using total variation, soft-thresholding and adaptive median filter, respectively. Finally, compare the PSNR values to analyse the denoising effect, edges preserving, and blurring.

並列關鍵字

Denoising ； Wavelet ； Soft-thresholding ； TV ； Adaptive Median Filter

參考文獻

[1] A. Chambolle, An algorithm for total variation minimization and applications,

[2] S. G. Chang, B. Yu, and M. Vetterli, Adaptive wavelet thresholding for

image denoising and compression, IEEE Transacions on Image Processing, 9

(2000), pp. 1532–1546.

Applied Mathematics, 1 ed., 1992.