DCT statistics model-based blind image quality assessment
- 1 September 2011
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 3093-3096
- https://doi.org/10.1109/icip.2011.6116319
Abstract
We propose an efficient, general-purpose, distortion-agnostic, blind/no-reference image quality assessment (NR-IQA) algorithm based on a natural scene statistics model of discrete cosine transform (DCT) coefficients. The algorithm is computationally appealing, given the availability of platforms optimized for DCT computation. We propose a generalized parametric model of the extracted DCT coefficients. The parameters of the model are utilized to predict image quality scores. The resulting algorithm, which we name BLIINDS-II, requires minimal training and adopts a simple probabilistic model for score prediction. When tested on the LIVE IQA database, BLIINDS-II is shown to correlate highly with human visual perception of quality, at a level that is even competitive with the powerful full-reference SSIM index.Keywords
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