Literature DB >> 10165355

Wavelet compression of medical imagery.

E Reiter1.   

Abstract

Wavelet compression is a transform-based compression technique recently shown to provide diagnostic-quality images at compression ratios as great as 30:1. Based on a recently developed field of applied mathematics, wavelet compression has found success in compression applications from digital fingerprints to seismic data. The underlying strength of the method is attributable in large part to the efficient representation of image data by the wavelet transform. This efficient or sparse representation forms the basis for high-quality image compression by providing subsequent steps of the compression scheme with data likely to result in long runs of zero. These long runs of zero in turn compress very efficiently, allowing wavelet compression to deliver substantially better performance than existing Fourier-based methods. Although the lack of standardization has historically been an impediment to widespread adoption of wavelet compression, this situation may begin to change as the operational benefits of the technology become better known.

Mesh:

Year:  1996        PMID: 10165355     DOI: 10.1089/tmj.1.1996.2.131

Source DB:  PubMed          Journal:  Telemed J        ISSN: 1078-3024


  2 in total

1.  Development and evaluation of a novel lossless image compression method (AIC: artificial intelligence compression method) using neural networks as artificial intelligence.

Authors:  Hiroshi Fukatsu; Shinji Naganawa; Shinnichiro Yumura
Journal:  Radiat Med       Date:  2008-04

2.  Design of a noise-dependent shrinkage function in wavelet shrinkage of X-ray CT image.

Authors:  Naruomi Yasuda; Yoshie Kodera
Journal:  Int J Comput Assist Radiol Surg       Date:  2009-05-01       Impact factor: 2.924

  2 in total

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