The following information was submitted:
Transactions: INTERNATIONAL JOURNAL of CIRCUITS, SYSTEMS and SIGNAL PROCESSING
Transactions ID Number: 20-611
Full Name: Peter Ndajah
Position: Ph.D. Candidate
Age: ON
Sex: Male
Address: Graduate School of Science and Technology, Niigata University, 8050, Ikarashi 2-no-cho, Nishi-ku, Niigata, 950-2181
Country: JAPAN
Tel: +818031495685
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E-mail address: ndajah@telecom0.eng.niigata-u.ac.jp
Other E-mails: ndajah@gmail.com
Title of the Paper: an investigation on the quality of denoised images
Authors as they appear in the Paper: Peter Ndajah, Hisakazu Kikuchi, Masahiro Yukawa, Hidenori Watanabe, Shogo Muramatsu
Email addresses of all the authors: ndajah@telecom0.eng.niigata-u.ac.jp,kikuchi@eng.niigata-u.ac.jp,yukawa@eng.niigata-u.ac.jp,hide-w@telecom0.eng.niigata-u.ac.jp,shogo@eng.niigata-u.ac.jp
Number of paper pages: 12
Abstract: The mean squared error (MSE) and its related metrics such as peak signal to noise ratio (PSNR), root mean squared error (RMSE) 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. Denoised image quality has also been traditionally measured in terms of the MSE or its derivatives. However, none of these metrics takes the structural fidelity of the image into account. We investigate the structural changes that occur during the denoising process and attempt to study an alternative metric for determining the quality of denoised images based on structural changes. We also show the shortcomings of the MSE-based image quality metrics.
Keywords: SSIM, MSE, TV, PSNR, Noise, Denoise, Metric
EXTENSION of the file: .pdf
Special (Invited) Session: SSIM Image Quality Metric for Denoised Images
Organizer of the Session: 638-241
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