Sentence examples for reference metrics and from inspiring English sources

The performance of this metric is evaluated with respect to full reference metrics and the metric in [14].

We can observe that the performance of our metric is comparable with the considered full reference metrics, and our metric outperforms PSNR in the case of both MPEG2 and H.264 compression and also in the case "IP distortion", i.e., the case of H.264 video transmitted over a network.

With the aid of the databases above, we compare the performance versus subjective tests of our metric with respect to the most popular full reference metrics and to the RR metrics with the best performance and whose results are directly comparable or reproducible.

Few additional measures were used to illustrate the performance of proposed algorithm such as cumulative probability of blur detection (CPBD) (no reference metrics) and normalized cross-correlation (NCC) (similarity based metrics).

In this article we propose a low complexity RR metric based on edge preservation which can be calculated in real time in practical image/video processing and transmission systems, performs comparably with the mostly used full reference metrics and requires a limited overhead for the transmission of side information.

Results highlight that the metric correlates well with subjective observations, also in comparison with commonly used full-reference metrics and with a state-of-the-art reduced reference metric.

The results highlight that the proposed metric correlates well with subjective observations, also in comparison with commonly used full-reference metrics and with a state-of-the-art metric.

Results highlight that the metric correlates well with subjective observations, also in comparison with commonly used full-reference metrics and with a state-of-the-art RR metric.

The correlation between 13 well-known full-reference metrics and perceived quality of compressed HDR content is investigated in [26].

Results highlight that the proposed metric well correlates with subjective observations, also in comparison with commonly used full-reference metrics and with state-of-the-art RR metrics.

Table 1 shows the LCC after the nonlinear fitting for the proposed and reference metrics for Datasets I and II.