41 OBJECTIVE VIDEO QUALITY ASSESSMENT

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Multiscale structural similarity for image quality assessment (2003, background): “Thus, these approaches must rely on a number of strong assumptions and generalizations [4],[5].”
An information fidelity criterion for image quality assessment using natural scene statistics (2005, methodology): “FR QA techniques proposed in the literature can be divided into two major groups: those based on the HVS and those based on arbitrary signal fidelity criteria (a detailed review of the research on FR QA methods can be found in [2]–[5]).”
Video quality assessment based on structural distortion measurement (2004, background): “Reviews on perceptual error sensitivity-based models can be found in [8], [23], [24].”
On the use of deep learning for blind image quality assessment (2016, background): “[2, 3, 4, 5, 6, 7], reducedreference image quality assessment (RR-IQA) algorithms, and no-reference/blind image quality assessment (NR-IQA) algo-”
A survey of visual sensor network platforms (2012, methodology): “We note that there are better models available in the literature [50].”