De-noising by soft-thresholding
IEEE Transactions on Information Theory
Adaptive wavelet thresholding for image denoising and compression
IEEE Transactions on Image Processing
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Wavelet transform is a recent signal analysis tool that is already been successfully used in image, video and speech compression applications. This paper looks at the Wavelet transform as a method of compressing computer network measurements produced from high-speed networks. Such networks produce a large amount of information over a long period of time, requiring compression for archiving. An important aspect of the compression is to maintain the quality in important features of signals. In this paper two known wavelet coefficient threshold selection techniques are examined and utilized separately along with an efficient method for storing wavelet coefficients. Experimental results are obtained to compare the behaviour of the two threshold selection schemes on delay and data rate signals, by using the mean square error (MSE) statistic, PSNR and the file size of the compressed output.