Title :
Application of Wavelet Threshold to Image De-noising
Author :
Li, Qingwu ; He, Chunyuan
Author_Institution :
Coll. of Comput. & Inf. Eng., Hohai Univ.
fDate :
Aug. 30 2006-Sept. 1 2006
Abstract :
Wavelet based techniques have been used for a number of years to de-noise images. By means of the wavelet packet analysis, the low frequency part and high frequency part of the super stratum can be concurrently further broken down, and therefore, more exact analysis of localities can be conducted. By thresholding the wavelet packet transform coefficients of the noisy image, the original image can be reconstructed correctly. Different threshold selections and thresholding methods are discussed. A novel cubic thresholding function is presented based on wavelet packet shrinkage. Quantifying the performance of image de-noising schemes by using the peak signal-to-noise ratio (PSNR) and mean square error (MSE), the performance of the cubic threshold scheme is compared with the hard and soft threshold schemes. The experiment shows that image de-noising using the cubic threshold performs better than that using the hard and soft threshold
Keywords :
image denoising; image reconstruction; image segmentation; mean square error methods; wavelet transforms; cubic thresholding function; image denoising; image reconstruction; image thresholding; mean square error; peak signal-to-noise ratio; wavelet packet shrinkage; wavelet packet transform; Application software; Discrete wavelet transforms; Frequency; Image denoising; Noise reduction; PSNR; Two dimensional displays; Wavelet analysis; Wavelet packets; Wavelet transforms;
Conference_Titel :
Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7695-2616-0
DOI :
10.1109/ICICIC.2006.238
