BBAND Index: A No-Reference Banding Artifact Predictor
This addresses video quality assessment for viewers and developers by improving banding artifact detection, though it is incremental as it builds on existing methods.
The paper tackled the problem of banding artifacts in video compression by proposing the BBAND index, a no-reference video quality model that predicts banding severity, and it outperformed state-of-the-art detection algorithms with better consistency to subjective evaluations.
Banding artifact, or false contouring, is a common video compression impairment that tends to appear on large flat regions in encoded videos. These staircase-shaped color bands can be very noticeable in high-definition videos. Here we study this artifact, and propose a new distortion-specific no-reference video quality model for predicting banding artifacts, called the Blind BANding Detector (BBAND index). BBAND is inspired by human visual models. The proposed detector can generate a pixel-wise banding visibility map and output a banding severity score at both the frame and video levels. Experimental results show that our proposed method outperforms state-of-the-art banding detection algorithms and delivers better consistency with subjective evaluations.