Banding vs. Quality: Perceptual Impact and Objective Assessment
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Abstract (arXiv)
Staircase-like contours introduced to a video by quantization in flat areas, commonly known as banding, have been a long-standing problem in both video processing and quality assessment communities. The fact that even a relatively small change of the original pixel values can result in a strong impact on perceived quality makes banding especially difficult to be detected by objective quality metrics. In this paper, we study how banding annoyance compares to more commonly studied scaling and compression artifacts with respect to the overall perceptual quality. We further propose a simple combination of VMAF and the recently developed banding index, CAMBI, into a banding-aware video quality metric showing improved correlation with overall perceived quality.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 22 Feb 2022.
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Citing papers per year: 2023: 3; 2024: 0; 2025: 1.
4 papers.
- 2023BAND-2k: Banding Artifact Noticeable Database for Banding Detection and Quality Assessmentcited by 5
- 2023FS-BAND: A Frequency-Sensitive Banding Detectorcited by 3
- 2023BVI-Artefact: An Artefact Detection Benchmark Dataset for Streamed Videoscited by 3
- 2025Subjective and Objective Quality Assessment of Banding Artifacts on Compressed Videoscited by 0
- 2025Subjective and Objective Quality Assessment of Banding Artifacts on Compressed Videos12 Aug 2025
- 2023BVI-Artefact: An Artefact Detection Benchmark Dataset for Streamed Videos14 Dec 2023
- 2023FS-BAND: A Frequency-Sensitive Banding Detector30 Nov 2023
- 2023BAND-2k: Banding Artifact Noticeable Database for Banding Detection and Quality Assessment29 Nov 2023
Similar, not cited
Close in wording, no citation either way
- 2021CAMBI: Contrast-aware Multiscale Banding Index
- 2025RIFLE: Removal of Image Flicker-Banding via Latent Diffusion Enhancement
- 2026Bricker to BRACE: A Bracket Exposure RAW Dataset and Restoration Model for Flicker-Banding
- 2026Seeing Beyond 8bits: Subjective and Objective Quality Assessment of HDR-UGC Videos
- 2023Towards Explainable In-the-Wild Video Quality Assessment: A Database and a Language-Prompted Approach
- 2025Guiding WaveMamba with Frequency Maps for Image Debanding
- 2021A Subjective Study on Videos at Various Bit Depths
- 2021Study of Compression Statistics and Prediction of Rate-Distortion Curves for Video Texture