Quantitative Models of Image Quality

Author:

Beaton Robert J.1

Affiliation:

1. Department of Industrial Engineering and Operations Research Virginia Polytechnic Institute and State University Blacksburg, Virginia 24061

Abstract

Fourteen image quality metrics were evaluated for hard-copy and soft-copy displays of digital images degraded by various levels of noise and blur. All quality metrics were formulated to include the displayed modulation spectrum of the image. The statistical analyses suggested that several of the metrics correlated strongly with performance, and, thus, support the proposed utility of image-dependent quality measures. An MTFA-type metric was shown to correlate highest with the average performance scores across noise and blur conditions.

Publisher

SAGE Publications

Subject

General Medicine

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Investigating U-Net's Reliability in Saliency Detection with Salt and Pepper Noise;2024 Third International Conference on Power, Control and Computing Technologies (ICPC2T);2024-01-18

2. Quantifying Salt and Pepper Noise Using Deep Convolutional Neural Network;Journal of The Institution of Engineers (India): Series B;2022-04-25

3. VBNC: Voting Based Noise Classification Framework Using Deep CNN;Conference Proceedings of ICDLAIR2019;2021

4. Evaluation of Subjective Image Quality with the Square Root Integral Method;Applied Vision;1989

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