Sentence examples for blocking and blurring from inspiring English sources

Our model is designed to calculate the distortions of blocking and blurring effects, which appeared from the coding operation.

These NR methods mainly measure blocking and blurring artifacts.

The focus is on the detection of blocking and blurring artifacts.

JPEG images may produce both blocking and blurring artifacts while JPEG2000 images mainly produce blurring artifacts.

Clearly, the linear combination of the proposed blocking and blur metrics showed the best performance.

II, the proposed blocking and blur metrics are explained, and then the image quality metric based on image classification is presented.

Table 4 shows the NR image quality metrics obtained as a linear combination of some blocking and blur metrics (global optimization).

Although these combinations of the blocking and blur metrics show good results, the NR image quality metric using the proposed NR blur and blocking metrics showed the best performance.

The experimental results show that the proposed NR blocking and blur metrics correlated highly with the subjective scores and the proposed NR metric based on image classification showed consistently good performance.

Jeong et al. optimized weights for blocking and blur metrics to compute the NR image quality metric as follows: Q N R = v 1 × B l o c k i n g M + v 2 × B l u r M (14).

The quality prediction is based on image features such as EPSNR, blocking, and blur.