Quality Modeling Under A Relaxed Natural Scene Statistics Model
Abstract: Information-theoretic image quality assessment (IQA) models such as Visual Information Fidelity (VIF) and Spatio-temporal Reduced Reference Entropic Differences (ST-RRED) have enjoyed great success by seamlessly integrating natural scene statistics (NSS) with information theory. The Gaussian Scale Mixture (GSM) model that governs the wavelet subband coefficients of natural images forms the foundation for these algorithms. However, the explosion of user-generated content on social media, which is typically distorted by one or more of many possible unknown impairments, has revealed the limitations of NSS-based IQA models that rely on the simple GSM model. Here, we seek to elaborate the VIF index by deriving useful properties of the Multivariate Generalized Gaussian Distribution (MGGD), and using them to study the behavior of VIF under a Generalized GSM (GGSM) model.
- Daniel L Ruderman, “The statistics of natural images,” Network: Computation in Neural Systems, vol. 5, no. 4, pp. 517–548, 1994.
- “Scale mixtures of gaussians and the statistics of natural images,” in International Conference on Neural Information Processing Systems. 1999, p. 855–861, MIT Press.
- “An information fidelity criterion for image quality assessment using natural scene statistics,” IEEE Transactions on Image Processing, vol. 14, no. 12, pp. 2117–2128, 2005.
- “Image information and visual quality,” IEEE Transactions on Image Processing, vol. 15, no. 2, pp. 430–444, 2006.
- “Toward a practical perceptual video quality metric,” The Netflix Tech Blog, vol. 6, 2016.
- R. Soundararajan and A. C. Bovik, “Video quality assessment by reduced reference spatio-temporal entropic differencing,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 23, no. 4, pp. 684–694, 2013.
- “SpEED-QA: Spatial efficient entropic differencing for image and video quality,” IEEE Signal Processing Letters, vol. 24, no. 9, pp. 1333–1337, 2017.
- “Blind image quality assessment: From natural scene statistics to perceptual quality,” IEEE Transactions on Image Processing, vol. 20, no. 12, pp. 3350–3364, 2011.
- “No-reference image quality assessment in the spatial domain,” IEEE Transactions on Image Processing, vol. 21, no. 12, pp. 4695–4708, 2012.
- “Making a “completely blind” image quality analyzer,” IEEE Signal Processing Letters, vol. 20, no. 3, pp. 209–212, 2013.
- Z. Sinno and A. C. Bovik, “Large-scale study of perceptual video quality,” IEEE Transactions on Image Processing, vol. 28, no. 2, pp. 612–627, 2019.
- “Ugc-video: Perceptual quality assessment of user-generated videos,” in IEEE Conference on Multimedia Information Processing and Retrieval, 2020, pp. 35–38.
- “UGC-VQA: Benchmarking blind video quality assessment for user generated content,” arXiv preprint arXiv:2005.14354, 2020.
- “Generalized Gaussian scale mixtures: A model for wavelet coefficients of natural images,” Signal Processing: Image Communication, vol. 66, pp. 87–94, 2018.
- “The steerable pyramid: A flexible architecture for multi-scale derivative computation,” in International Conference on Image Processing. IEEE, 1995, vol. 3, pp. 444–447.
- C.E. Shannon, “A mathematical theory of communication,” The Bell System Technical Journal, vol. 27, no. 3, pp. 379–423, 1948.
- J. Fahs and I. Abou-Faycal, “A new tight upper bound on the entropy of sums,” Entropy, vol. 17, no. 12, pp. 8312–8324, 2015.
- “On the sum of generalized gaussian random signals,” in International Conference on Signal Processing, 2004, vol. 1, pp. 50–53 vol.1.
- H. Soury and M. Alouini, “New results on the sum of two generalized gaussian random variables,” in IEEE Global Conference on Signal and Information Processing, 2015, pp. 1017–1021.
- K. V. Mardia, “Measures of multivariate skewness and kurtosis with applications,” Biometrika, vol. 57, no. 3, pp. 519–530, 1970.
- “A multivariate generalization of the power exponential family of distributions,” Communications in Statistics - Theory and Methods, vol. 27, no. 3, pp. 589–600, 1998.
- T. Kollo, “Multivariate skewness and kurtosis measures with an application in ica,” Journal of Multivariate Analysis, vol. 99, no. 10, pp. 2328–2338, 2008.
- “The location-scale mixture exponential power distribution: A Bayesian and maximum likelihood approach,” Journal of Applied Mathematics, vol. 2012, pp. 978282, Oct 2012.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.