Abstract
This paper presents the performance evaluation of image and video quality assessment metrics on two publicly available datasets with subjective quality ratings. In addition to the performance analysis at the global level - at the level of complete datasets, the paper presents the objective measures performance evaluation on subsets of signals inside them. The image dataset contains five subsets created by using different types of JPEG compression, while the video dataset contains six subsets of sequences - four created by compression of original sequences, and two subsets are with video signal transmission characteristic degradations. To determine the success of objective measures, i.e. comparison of subjective and objective quality scores, there were used measures accepted by the International Telecommunication Union - ITU (linear correlation coefficient, rank-order correlation coefficient, mean absolute error, root mean squared error and outlier ratio). It was shown that objective quality measures can reach a high level of agreement with the results of subjective tests on subsets of datasets. Objective measures performances depend on the type of degradation which significantly affects the performance at the complete dataset level. The difference in performances is more pronounced on video sequences due to considerable visual differences in sequences created by using compression, packet losses and additive Gaussian noise. Therefore, we can say that a universal objective measure, i.e. measure that is useful for different types of signal degradation, for different degradation levels, and for different applications currently does not exist.
Highlights
Images, or videos, pass numerous processing and transmission phases before being viewed by the observer, and each of the phases may enter degradations that affect the quality of the final presentation
According to the amount of information of the original image used in the quality assessment process on the receiving side, objective image quality evaluation can be divided into three categories: no-reference (NR), full-reference (FR) and reduced-reference (RR) (Bovik, 2013)
This paper analyzed a possibility of using the full-reference objective quality assessment measures of visual signals – images and videos
Summary
Videos, pass numerous processing and transmission phases before being viewed by the observer, and each of the phases may enter degradations that affect the quality of the final presentation. According to the amount of information of the original (source, reference) image used in the quality assessment process on the receiving side (observer side), objective image quality evaluation can be divided into three categories: no-reference (NR), full-reference (FR) and reduced-reference (RR) (Bovik, 2013). The original image/video usually comes from a high quality sensor and as such requires much more resources than image/video after compression For this reason, FR quality assessment measures are used in laboratory tests to select image and video processing techniques. Some of the objective measures were analyzed for the first time in the quality assessment of high-resolution images (JPEG XR Image Dataset), and in the quality evaluation of the sequences with H.265 compression (CSIQ Video Dataset).
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