J - F . Lerallut

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We present an analysis of different filter banks for the compression of magnetic resonance (MR) images of the human brain using wavelet packets based on biorthogonal filters. Initially, peak signal to noise ratio (PSNR) and normalized root mean square (RMS) error criteria are calculated for a series of images compressed with a 33:1 ratio, using filter banks(More)
We present an analysis of the characteristics of different filters for the compression of magnetic resonance images. Compression rates were 33:1 and 50:1. We compare the performance among different types of wavelets presented in the literature and provide quantitative (percentage of energy retained, peak signal to noise ratio) and qualitative (analysis by a(More)
We present an analysis of the characteristics of different filters for the compression of magnetic resonance images. Compression rates were 33:1 and 50:1. We compare the performance among different types of wavelets presented in the literature and provide quantitative (percentage of energy retained, peak signal to noise ratio) and qualitative (analysis by a(More)
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