The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Why is image quality assessment so difficult?
Abstract
Image quality assessment plays an important role in various image processing applications. A great deal of effort has been made in recent years to develop objective image quality metrics that correlate with perceived quality measurement. Unfortunately, only limited success has been achieved. In this paper, we provide some insights on why image quality assessment is so difficult by pointing out the weaknesses of the error sensitivity based framework, which has been used by most image quality assessment approaches in the literature. Furthermore, we propose a new philosophy in designing image quality metrics: The main function of the human eyes is to extract structural information from the viewing field, and the human visual system is highly adapted for this purpose. Therefore, a measurement of structural distortion should be a good approximation of perceived image distortion. Based on the new philosophy, we implemented a simple but effective image quality indexing algorithm, which is very promising as shown by our current results.
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Cites
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Cited by
Image quality assessment: from error visibility to structural similarity
Wang, Z., Bovik, A. C., Sheikh, H. R., & Simoncelli, E. P. (2004) · IEEE Transactions on Image Processing · doi:10.1109/tip.2003.819861 · Cited by 57,892
Self-citationVideo quality assessment based on structural distortion measurement
Wang, Z., Lu, L., & Bovik, A. C. (2004) · Signal Processing: Image Communication · doi:10.1016/s0923-5965(03)00076-6 · Cited by 1,024
Self-citationModern Image Quality Assessment
Wang, Z., & Bovik, A. C. (2006) · Synthesis Lectures on Image, Video, and Multimedia Processing · doi:10.1007/978-3-031-02238-8 · Cited by 967
Self-citationNo-reference perceptual quality assessment of JPEG compressed images
Wang, Z., Sheikh, H. R., & Bovik, A. C. (2003) · Proceedings. International Conference on Image Processing · doi:10.1109/icip.2002.1038064 · Cited by 834
Self-citationEnd-to-End Adversarial Retinal Image Synthesis
Costa, P., Galdran, A., Meyer, M. I., Niemeijer, M., Abramoff, M., Mendonca, A. M., & Campilho, A. (2018) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2017.2759102 · Cited by 432
Metadata
- Authors
- Wang, Z., Bovik, & Lu, L.
- Venue
- IIEEE International Conference on Acoustics Speech and Signal Processing
- Publisher
- IEEE
- Published
- 2002
- Pages
- IV-IV
- ISSN
- 1520-6149 (ISSN-L)
- OpenAlex
- W2158564760
- Cited by
- 786
- References
- 10
- FWCI
- 10.26
- Type
- conference paper
- Language
- en
- Open access
- closed
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