# BBAND Index: A No-Reference Banding Artifact Predictor

arXiv: https://arxiv.org/abs/2002.11891 · HTML: https://mlsanity.com/paper/2002.11891/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Feb 2020.

## Built on by (most cited first, 19 of 19)

- [RAPIQUE: Rapid and Accurate Video Quality Prediction of User Generated Content](https://mlsanity.com/paper/2101.10955/) (2021)
- [Subjective Assessment of High Dynamic Range Videos Under Different Ambient Conditions](https://mlsanity.com/paper/2209.10005/) (2022)
- [CLIPVQA:Video Quality Assessment via CLIP](https://mlsanity.com/paper/2407.04928/) (2024)
- [FAVER: Blind Quality Prediction of Variable Frame Rate Videos](https://mlsanity.com/paper/2201.01492/) (2022)
- [CAMBI: Contrast-aware Multiscale Banding Index](https://mlsanity.com/paper/2102.00079/) (2021)
- [Just Noticeable Difference for Large Multimodal Models](https://mlsanity.com/paper/2507.00490/) (2025)
- [BAND-2k: Banding Artifact Noticeable Database for Banding Detection and Quality Assessment](https://mlsanity.com/paper/2311.17752/) (2023)
- [Regression or Classification? New Methods to Evaluate No-Reference Picture and Video Quality Models](https://mlsanity.com/paper/2102.00155/) (2021)
- [BrokenVideos: A Benchmark Dataset for Fine-Grained Artifact Localization in AI-Generated Videos](https://mlsanity.com/paper/2506.20103/) (2025)
- [Robust estimation of exposure ratios in multi-exposure image stacks](https://mlsanity.com/paper/2308.02968/) (2023)
- [FS-BAND: A Frequency-Sensitive Banding Detector](https://mlsanity.com/paper/2311.18216/) (2023)
- [BVI-Artefact: An Artefact Detection Benchmark Dataset for Streamed Videos](https://mlsanity.com/paper/2312.08859/) (2023)
- [Deep Image Debanding](https://mlsanity.com/paper/2110.08569/) (2021)
- [MVAD: A Multiple Visual Artifact Detector for Video Streaming](https://mlsanity.com/paper/2406.00212/) (2024)
- [Subjective and Objective Analysis of Indian Social Media Video Quality](https://mlsanity.com/paper/2401.02794/) (2024)
- [Redistributing the Precision and Content in 3D-LUT-based Inverse Tone-mapping for HDR/WCG Display](https://mlsanity.com/paper/2309.17160/) (2023)
- [Subjective and Objective Quality Assessment of Banding Artifacts on Compressed Videos](https://mlsanity.com/paper/2508.08700/) (2025)
- [Guiding WaveMamba with Frequency Maps for Image Debanding](https://mlsanity.com/paper/2508.11331/) (2025)
- [Towards Unified Video Quality Assessment](https://mlsanity.com/paper/2512.02224/) (2025)

## Abstract (arXiv)

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.