REGIS, C. D. M.; http://lattes.cnpq.br/3729525547666162; REGIS, Carlos Danilo Miranda.
Resumo:
Digital videos are subject to several types of distortions, which may occur during the
processes of acquisition, processing, compression, storage and transmission of videos,
resulting in loss of visual quality. Video quality assessment is important to set system
parameters and propose the reduction of degradation, to improve the systems quality.
The most appropriate way to assess the visual quality of a video sequence is subjective
assessment. However, objective assessment is quicker and cheaper in comparison
with the subjective solutions.
The development of objective metrics has increased significantly, because of the need
to quantify appropriately the visual quality perceived by the Human Visual System
(HVS). The production of 3D videos is increasing, as well as the need to evaluate
them. A problem identified in the evaluation process is related to the methods used for
2D videos, which are not suitable for measuring the quality of 3D videos, since typical
depth and distortions of the stereoscopy are not considered.
This study proposes new metrics for assessment of 2D and 3D videos. The proposed
metric uses spatial and temporal information and disparity to evaluate videos more
closely to the subjective assessment.
In order to obtain the metric for 3D videos, measurements have been proposed for
2D videos, which uses spatial information (PW-SSIM – Perceptual Weighted Video
Quality Approach) and temporal information (TPW-SSIM – Temporal Perceptual
Weighted Video Quality Approach). Based on these metrics, the DPW–SSIM (Disparity
Perceptual Weighted Video Quality Approach) and the DTPW-SSIM metrics
(Disparity Temporal Perceptual Weighted Video Quality Approach metrics) have been
proposed to assess 3D videos.
For the evaluation of two dimensional videos the B-SSIM metric obtained the best
result for blurry images. For MPEG-2 encoded videos, transmitted by wireless and
IP systems, the metric with the best result was the TPW-SSIM. Regarding the three
dimensional videos, the metrics that included disparity exceeded the metrics that did
not include it, and the best results were obtained for the DPW-SSIM and PW-SSIM
metrics.