Literature DB >> 14517721

Quality degradation in lossy wavelet image compression.

Tzong-Jer Chen1, Keh-Shih Chuang, Jay Wu, Sharon C Chen, Ing-Ming Hwang, Meei-Ling Jan.   

Abstract

The objective of this study was to develop a method for measuring quality degradation in lossy wavelet image compression. Quality degradation is due to denoising and edge blurring effects that cause smoothness in the compressed image. The peak Moran z histogram ratio between the reconstructed and original images is used as an index for degradation after image compression. The Moran test is applied to images randomly selected from each medical modality, computerized tomography, magnetic resonance imaging, and computed radiography and compressed using the wavelet compression at various levels. The relationship between the quality degradation and compression ratio for each image modality agrees with previous reports that showed a preference for mildly compressed images. Preliminary results show that the peak Moran z histogram ratio can be used to quantify the quality degradation in lossy image compression. The potential for this method is applications for determining the optimal compression ratio (the maximized compression without seriously degrading image quality) of an image for teleradiology.

Mesh:

Year:  2003        PMID: 14517721      PMCID: PMC3046470          DOI: 10.1007/s10278-003-1652-0

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  16 in total

1.  Acceptable levels of digital image compression in chest radiology.

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Journal:  Australas Radiol       Date:  2000-02

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Journal:  Radiology       Date:  2000-05       Impact factor: 11.105

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Journal:  Phys Med Biol       Date:  1994-09       Impact factor: 3.609

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Journal:  IEEE Trans Med Imaging       Date:  1994       Impact factor: 10.048

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Authors:  B Zhao; L H Schwarz; P K Kijewski
Journal:  Med Phys       Date:  1998-09       Impact factor: 4.071

6.  The effects of lossy compression on the detection of subtle pulmonary nodules.

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Journal:  Med Phys       Date:  1996-01       Impact factor: 4.071

7.  An analytical look at the effects of compression on medical images.

Authors:  K Persons; P Palisson; A Manduca; B J Erickson; V Savcenko
Journal:  J Digit Imaging       Date:  1997-08       Impact factor: 4.056

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Authors:  K S Chuang; B J Liu; H K Huang; H Yonekawa; A Sankaran
Journal:  Radiographics       Date:  1994-03       Impact factor: 5.333

9.  Subjective and objective assessment of image quality--a comparison.

Authors:  W F Good; D Gur; J H Feist; F L Thaete; C R Fuhrman; C A Britton; B S Slasky
Journal:  J Digit Imaging       Date:  1994-05       Impact factor: 4.056

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Authors:  J A Swets
Journal:  Invest Radiol       Date:  1979 Mar-Apr       Impact factor: 6.016

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  3 in total

1.  Extreme compression for extreme conditions: pilot study to identify optimal compression of CT images using MPEG-4 video compression.

Authors:  P Gabriel Peterson; Sung K Pak; Binh Nguyen; Genevieve Jacobs; Les Folio
Journal:  J Digit Imaging       Date:  2012-12       Impact factor: 4.056

2.  A blurring index for medical images.

Authors:  Tzong-Jer Chen; Keh-Shih Chuang; Jen-Hao Chang; Ya-Hui Shiao; Chun-Chao Chuang
Journal:  J Digit Imaging       Date:  2006-06       Impact factor: 4.056

3.  Quality of compressed medical images.

Authors:  Ya-Hui Shiao; Tzong-Jer Chen; Keh-Shih Chuang; Cheng-Hsun Lin; Chun-Chao Chuang
Journal:  J Digit Imaging       Date:  2007-02-22       Impact factor: 4.056

  3 in total

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