The intended receiver of video signals is the human eye, in an overwhelmingly large number of applications. Perceptual video quality assessment algorithms attempt to algorithmically or objectively assess the quality of a video signal as judged by a human observer.
Video quality assessment algorithms in the literature are simple extensions of still image metrics. While reasonable results can be obtained using simple extensions of established still image quality metrics for video signals, videos contain many artifacts that are specific to motion or that are largely temporal, such as ghosting, jitter, jerkiness, etc. Motion information plays a key role in visual perception of video signals since the human eye is extremely sensitive to motion and can accurately judge the velocity and direction of moving objects. Thus, modeling of motion and motion artifacts in video signals can lead to improvement in the performance of video quality assessment algorithms. My research focuses on developing algorithms for video quality assessment using new models for natural video statistics and video motion.
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Book chapters
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[1]
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Kalpana Seshadrinathan and Alan C. Bovik.
Video quality assessment.
In A. .C. Bovik, editor, The Essential Guide to Video
Processing, pages 417-436. Academic Press, 2009.
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[2]
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K. Seshadrinathan, R. J. Safranek, J. Chen, T. N. Pappas, H. R. Sheikh, E. P.
Simoncelli, Z. Wang, and A. C. Bovik.
Image quality assessment.
In A. .C. Bovik, editor, The Essential Guide to Video
Processing, pages 553-596. Academic Press, 2009.
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[3]
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Kalpana Seshadrinathan and Alan C. Bovik.
Advances in image and video quality assessment.
In B. Furht, editor, The Encyclopedia of Multimedia, pages
8-17. Springer Publications, 2009.
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[4]
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Kalpana Seshadrinathan and Alan C. Bovik.
Image and video quality assessment.
In B. Furht, editor, The Encyclopedia of Multimedia, pages
8-17. Springer Publications, 2009.
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[5]
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R. Soundararajan, Kalpana Seshadrinathan, and Alan C. Bovik.
Video quality assessment for wireless applications.
In B. Furht, editor, The Encyclopedia of Multimedia, pages
953-937. Springer Publications, 2009.
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[6]
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Kalpana Seshadrinathan, Hamid Rahim Sheikh, Alan C. Bovik, and Zhou Wang.
Structural and information theoretic approaches to image quality
assessment.
In Rick S. Blum and Zheng Liu, editors, Multisensor image fusion
and its applications, pages 473-499. Taylor and Francis, 2006.
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[7]
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Kalpana Seshadrinathan and Alan C. Bovik.
Image and video quality assessment.
In B. Furht, editor, The encyclopedia of multimedia, pages
288-299. Springer Publications, 2005.
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Journal articles
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[1]
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K. Seshadrinathan and A. C. Bovik.
Unified treatment of full reference image quality assessment
algorithms.
IEEE Transactions on Image Processing, 20010.
(in preparation).
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[2]
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K. Seshadrinathan, R. Soundararajan, A. C. Bovik, and L. K. Cormack.
Study of subjective and objective quality assessment of video.
IEEE Transactions on Image Processing, 2009.
(accepted).
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[3]
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K. Seshadrinathan and A. C. Bovik.
Motion tuned spatio-temporal quality assessment of natural videos.
IEEE Transactions on Image Processing, 2009.
(accepted).
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Magazine articles
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[1]
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S. Channappayya, K. Seshadrinathan, and A. C. Bovik.
Video quality assessment with motion and temporal artifacts
considered.
In EE times, 2007.
[ .pdf ]
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Conference articles
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[1]
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K. Seshadrinathan, R. Soundararajan, A. C. Bovik, and L. K. Cormack.
A subjective study to evaluate video quality assessment algorithms.
In SPIE Proceedings Human Vision and Electronic Imaging, 2010.
(submitted).
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[2]
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K. Seshadrinathan and A. C. Bovik.
Motion-based perceptual quality assessment of video.
In SPIE Proceedings Human Vision and Electronic Imaging, 2009.
[ .pdf ]
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[3]
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Kalpana Seshadrinathan and Alan C. Bovik.
Unifying analysis of full reference image quality assessment.
In IEEE Intl. Conf. on Image Proc., 2008.
[ .pdf ]
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[4]
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R. Soundararajan, Kalpana Seshadrinathan, and Alan C. Bovik.
Quality assessment of digital videos.
In Texas Instruments Developers Conference on Consumer
Electronics, February 2008.
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[5]
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Kalpana Seshadrinathan and Alan C. Bovik.
Multi-scale and scalable video quality assessment.
In IEEE International Conference on Consumer Electronics,
January 2008.
[ .pdf ]
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[6]
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Kalpana Seshadrinathan and Alan C. Bovik.
A structural similarity metric for video based on motion models.
In IEEE Intl. Conf. on Acoustics, Speech, and Signal Proc.,
2007.
[ .pdf ]
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[7]
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Kalpana Seshadrinathan and Alan C. Bovik.
Image and video quality assessment.
In Texas Instruments Developer's Conference, 2007.
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[8]
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Kalpana Seshadrinathan and Alan C. Bovik.
New vistas in image and video quality assessment.
In SPIE Proceedings Human Vision and Electronic Imaging,
January 2007.
[ .pdf ]
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[9]
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Kalpana Seshadrinathan and Alan C. Bovik.
An information theoretic video quality metric based on motion models.
In Third Intl. Workshop on Video Proc. and Quality Metrics for
Consumer Electronics, January 2007.
[ .pdf ]
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[10]
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Kalpana Seshadrinathan and Alan C. Bovik.
Statistical video models and their application to quality assessment.
In Second International Workshop on Video Processing and Quality
Metrics for Consumer Electronics, Scottsdale, Arizona, January 2006.
[ .pdf ]
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[11]
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Kalpana Seshadrinathan, H. R. Sheikh, and A. C. Bovik.
Detecting spread spectrum watermarks using natural scene statistics.
In IEEE Intl. Conf. on Image Proc., volume 2, pages 1106-9,
September 2005.
[ .pdf ]
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