Mutual Information Correlation with Human Vision in Medical Image Compression

Author(s): Li-Hui Lin, Tzong-Jer Chen*

Journal Name: Current Medical Imaging
Formerly: Current Medical Imaging Reviews

Volume 14 , Issue 1 , 2018

Become EABM
Become Reviewer
Call for Editor

Graphical Abstract:


Background: The lossy compression algorithm produces different results in various contrasts areas. Low contrast area image quality declines greater than that of high contrast regions using equal compression ratio. These results were obtained in a subjective study. The objective image quality metrics are more effective if the calculation method is more closely related to the human vision results.

Methods: This study first measured the PSNR and MI for discrimination between different contrast areas responding to lossy image compression in a SMPTE electronic pattern. The MI was consistent with human vision results in SMPTE electronic phantom but PSNR was not. The measurement was also applied to compressed medical images in different contrast cropping regions.

Results: The MI was found to be close to human vision in CT and MR but not CRX. Both weighted PSNR and weighted MI were created to respond to the gray value and the contrast areas affected the quality estimation.

Conclusion: The W-PSNR and W-MI showed that they can discriminate between different contrast areas using image compression ratios and the series of lines are equal to the contrast values and better than the tranditional approach. The W-MI measures were found to perform better than WPSNR and can be used as an image quality index.

Keywords: JPEG2000, medical image compression, image quality, mutual information, PSNR, W-MI measures.

open access plus

Rights & PermissionsPrintExport Cite as

Article Details

Year: 2018
Published on: 03 October, 2017
Page: [64 - 70]
Pages: 7
DOI: 10.2174/1573405613666171003151036

Article Metrics

PDF: 42