SSIM image quality metric for denoised images

Peter Ndajah, Hisakazu Kikuchi, Masahiro Yukawa, Hidenori Watanabe, Shogo Muramatsu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (Scopus)

Abstract

The mean square error (MSE) and its related metrics such as peak signal to noise ratio (PSNR), root mean square error (RMSE), mean absolute error (MAE), and signal to noise ratio (SNR) have been the basis for mathematically defined image quality measurement for a long time. These methods are all based on the MSE. Denoisng quality has also been traditionally measured in terms of the MSE or its derivatives. But none of these metrics takes the structural fidelity of the image into account. Here, we investigate the structural changes that occur during the denoising process. In particular, we ascertain the structural fidelity of TV-denoised images.

Original languageEnglish
Title of host publicationInternational Conference on Visualization, Imaging and Simulation - Proceedings
Pages53-57
Number of pages5
Publication statusPublished - 2010
Externally publishedYes
Event3rd WSEAS International Conference on Visualization, Imaging and Simulation, VIS'10 - Faro, Portugal
Duration: 2010 Nov 32010 Nov 5

Other

Other3rd WSEAS International Conference on Visualization, Imaging and Simulation, VIS'10
CountryPortugal
CityFaro
Period10/11/310/11/5

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Keywords

  • DENOISE
  • METRIC
  • MSE
  • NOISE
  • PSNR
  • SSIM
  • TV

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Modelling and Simulation

Cite this

Ndajah, P., Kikuchi, H., Yukawa, M., Watanabe, H., & Muramatsu, S. (2010). SSIM image quality metric for denoised images. In International Conference on Visualization, Imaging and Simulation - Proceedings (pp. 53-57)