The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
No-reference perceptual quality assessment of JPEG compressed images
Abstract
Human observers can easily assess the quality of a distorted image without examining the original image as a reference. By contrast, designing objective No-Reference (NR) quality measurement algorithms is a very difficult task. Currently, NR quality assessment is feasible only when prior knowledge about the types of image distortion is available. This research aims to develop NR quality measurement algorithms for JPEG compressed images. First, we established a JPEG image database and subjective experiments were conducted on the database. We show that Peak Signal-to-Noise Ratio (PSNR), which requires the reference images, is a poor indicator of subjective quality. Therefore, tuning an NR measurement model towards PSNR is not an appropriate approach in designing NR quality metrics. Furthermore, we propose a computational and memory efficient NR quality assessment model for JPEG images. Subjective test results are used to train the model, which achieves good quality prediction performance.
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Cites
Why is image quality assessment so difficult?
Wang, Z., Bovik, & Lu, L. (2002) · IIEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2002.1004620 · Cited by 786
Self-citationBlind measurement of blocking artifacts in images
Wang, Z., Bovik, A. C., & Evan, B. L. (2002) · Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101) · doi:10.1109/icip.2000.899622 · Cited by 413
Self-citationA generalized block-edge impairment metric for video coding
Wu, H. R., & Yuen, M. (1997) · IEEE Signal Processing Letters · doi:10.1109/97.641398 · Cited by 316
Perceptual Criteria for Image Quality Evaluation
Pappas, T. N., Safranek, R. J., & Chen, J. (2005) · Handbook of Image and Video Processing · doi:10.1016/b978-012119792-6/50118-2 · Cited by 289
DCT-domain blind measurement of blocking artifacts in DCT-coded images
Bovik, A. C., & Liu, S. (2002) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2001.941272 · Cited by 106
Self-citationObjective assessment of MPEG-video quality: a neural-network approach
Gastaldo, P., Rovetta, S., & Zunino, R. (2002) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2001.939572 · Cited by 19
Cited by
Blind Image Quality Assessment: From Natural Scene Statistics to Perceptual Quality
Moorthy, A. K., & Bovik, A. C. (2011) · IEEE Transactions on Image Processing · doi:10.1109/tip.2011.2147325 · Cited by 1,763
Self-citationA Two-Step Framework for Constructing Blind Image Quality Indices
Moorthy, A. K., & Bovik, A. C. (2010) · IEEE Signal Processing Letters · doi:10.1109/lsp.2010.2043888 · Cited by 1,196
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-citationUnsupervised feature learning framework for no-reference image quality assessment
Ye, P., Kumar, J., Kang, L., & Doermann, D. (2012) · 2012 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2012.6247789 · Cited by 785
Photo and Video Quality Evaluation: Focusing on the Subject
Luo, Y., & Tang, X. (2008) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-88690-7_29 · Cited by 444
Metadata
- Authors
- Wang, Z., Sheikh, H. R., & Bovik, A. C.
- Venue
- Proceedings. International Conference on Image Processing
- Publisher
- IEEE
- Published
- 2003-06-25
- Volume
- 1
- Pages
- I-477-I-480
- ISSN
- 1522-4880 (ISSN-L)
- OpenAlex
- W2107476778
- Cited by
- 834
- References
- 6
- FWCI
- 17.03
- Type
- conference paper
- Language
- en
- Open access
- closed
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