A computationally efficient video quality assessment method based on linear regression analysis

Sections 1 and 2 of the full paper explain the assessment method mentioned in the title, which we believe is more computationally efficient than existing ones. Section 1 briefs the state of the art. Section 2 is entitled "No-Reference Video Sequence Quality Assessment Model"; it needs to be divided into four subsections. Its core consists of; (1) we employ two parameters; the bit rate for each inter-coded frame and the difference between the inter-coded frame and its reference frame; (2) we carry out the linear regression analysis of the two parameters to assess the quality of a video sequence. Section 3 did experiments on five standard CIF video sequences to verify the effectiveness of our assessment method; the experimental results, given in Figs. 3 and 4 and Table 1, and their analysis show preliminarily that: (1) our assessment method is indeed more computationally efficient than existing ones and does not require the original video sequence for reference; (2) the assessment results obtained with our assessment method, which falls into the category of objective quality assessment, are very close to those obtained with the subjective assessment method.