# CAMBI: Contrast-aware Multiscale Banding Index

arXiv: https://arxiv.org/abs/2102.00079 · HTML: https://mlsanity.com/paper/2102.00079/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 21 references that are in the map.
- First posted on arXiv 29 Jan 2021.

## Builds on (most cited first, 2 of 2)

- [BBAND Index: A No-Reference Banding Artifact Predictor](https://mlsanity.com/paper/2002.11891/) (2020)
- [GIFnets: Differentiable GIF Encoding Framework](https://mlsanity.com/paper/2006.13434/) (2020)

## Built on by (most cited first, 9 of 9)

- [BAND-2k: Banding Artifact Noticeable Database for Banding Detection and Quality Assessment](https://mlsanity.com/paper/2311.17752/) (2023)
- [BrokenVideos: A Benchmark Dataset for Fine-Grained Artifact Localization in AI-Generated Videos](https://mlsanity.com/paper/2506.20103/) (2025)
- [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 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 artifacts are artificially-introduced contours arising from the quantization of a smooth region in a video. Despite the advent of recent higher quality video systems with more efficient codecs, these artifacts remain conspicuous, especially on larger displays. In this work, a comprehensive subjective study is performed to understand the dependence of the banding visibility on encoding parameters and dithering. We subsequently develop a simple and intuitive no-reference banding index called CAMBI (Contrast-aware Multiscale Banding Index) which uses insights from Contrast Sensitivity Function in the Human Visual System to predict banding visibility. CAMBI correlates well with subjective perception of banding while using only a few visually-motivated hyperparameters.