A.2.1.4 frame type detection, A.2.1.5 per-frame quality analysis, A.2.1.6 perceptual quality model – EXFO EXpert IPTV Test Tools (FTB-1 / 2 Pro) User Manual

Page 57

Advertising
background image

57

A.2.1.4

Frame Type Detection

VQmon/HD identifies individual I, P, and B frames in the GoP and measures the packet loss

rate and loss distribution occurring in each frame type. For unencrypted video streams,

VQmon/HD performs picture header decoding to identify individual frames, GoP size, and

frame rate. For encrypted/scrambled streams, heuristic algorithms are applied in order to

detect frame boundaries and measure frame size.

As mentioned in Section 2.1.1.1, the GoP structure has impact on both the efficiency of video

encoding and the robustness of encoded video. VQmon/HD takes the different I, P, and B

frame packet loss/discard rates into account when calculating perceptual video quality

metrics.

A.2.1.5

Per-frame Quality Analysis

VQmon/HD performs per-frame quality calculation using the frame type, frame size, codec

type, video bandwidth, and packet loss data. The proportion of each frame type impaired by

loss/discard is reported, along with the proportion of B and P frames impaired due to the
propagation of errors from earlier reference (I or P) frames in the GoP

.

A.2.1.6

Perceptual Quality Model

VQmon/HD’s perceptual quality model calculates estimated perceptual quality (MOS) scores

using the per-frame quality metrics and content analysis as inputs. The calculation model

considers the sensitivity of the content to quality degradation (e.g., that frame freezes

occurring during a high-motion scene will be more visible and annoying than those occurring

during a static scene) and other subjective factors such as viewer reaction time, recency, and

temporal masking (see Section 2.1.3.2).

Advertising