No reference video quality estimation based on human visual system for 2.5/3g devices

摘要: 2.5/3G devices should achieve satisfactory QoS, overcoming mobile standards drawbacks. In-service/blind quality monitoring is essential in order to improve perceptual according Human Visual System. Several techniques have been proposed for image/video assessment. A novel no-reference index which uses an effective HVS model proposed. Luminance masking, Contrast Sensitivity Function and temporal masking are taken into account with fast in-service algorithms. The able assess blockiness distortion a image-domain measure. Compression/post-processing blurring effects measured standard approach. Moving artifacts evaluated taking deviation respect natural image statistical model. effects, wireless noisy channels low video-streaming/playback bit rates (e.g. edge busyness persistence) evaluated. multi-level pooling algorithm (block, temporal-window, frame, sequence levels) used. Validation tests developed performance computational complexity. final measure provides human-like threshold-effect high correlation subjective data. Low complexity algorithms can be derived real-time, HVS-based, QoS management low-power consumer devices. Different ringing jerkiness) easily included.