Fast Video Recoloring via Curve-based Palettes

Color grading, as a crucial step in film post-production, plays an important role in emotional expression and artistic enhancement. Recently, a geometric palette-based approach to video recoloring has been introduced with impressive results. It offers an intuitive interface that allows users to alter the color of a video by manipulating a limited set of representative colors. However, this method has two primary limitations. Firstly, palette extraction is computationally expensive, often taking more than one hour to generate palettes even for medium-length videos, which significantly limits the practical application of color editing for longer videos. Secondly, the palette colors are less representative, and some primary colors may be omitted from the resulting palettes during topological simplification, making it less intuitive in color editing. To overcome these limitations, in this paper, we propose a novel approach to video recoloring. The core of our method is a set of Bézier curves that connect the dominant colors throughout the input video. By slicing these Bézier curves in RGBT space, per-frame palette can be naturally derived. During recoloring, users can select several frames of interest and modify their corresponding palettes to change the color of the video. Our method is simple and intuitive, enabling compelling time-varying recoloring results. Compared to existing methods, our approach is more efficient in palette extraction and can effectively capture the dominant colors of the video. Extensive experiments demonstrate the effectiveness of our method.

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Publication Details

Journal
IEEE Transactions on Image Processing
Published
2025-01-01
DOI
https://doi.org/10.1109/tip.2025.3607584
Primary Topic
Image Processing Techniques and Applications
Type
article
Field-Weighted Citation Impact
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article

Fast Video Recoloring via Curve-based Palettes

Kun Xu, Zhicheng Huang, Jiawei Zhou, Kang Li et al.
IEEE Transactions on Image Processing
Image Processing Techniques and Applications
article

Fast Video Recoloring via Curve-based Palettes

Kun Xu, Zhicheng Huang, Jiawei Zhou, Kang Li, Jian-Yu Hao, Zheng-Jun Du
article en

Abstract

Color grading, as a crucial step in film post-production, plays an important role in emotional expression and artistic enhancement. Recently, a geometric palette-based approach to video recoloring has been introduced with impressive results. It offers an intuitive interface that allows users to alter the color of a video by manipulating a limited set of representative colors. However, this method has two primary limitations. Firstly, palette extraction is computationally expensive, often taking more than one hour to generate palettes even for medium-length videos, which significantly limits the practical application of color editing for longer videos. Secondly, the palette colors are less representative, and some primary colors may be omitted from the resulting palettes during topological simplification, making it less intuitive in color editing. To overcome these limitations, in this paper, we propose a novel approach to video recoloring. The core of our method is a set of Bézier curves that connect the dominant colors throughout the input video. By slicing these Bézier curves in RGBT space, per-frame palette can be naturally derived. During recoloring, users can select several frames of interest and modify their corresponding palettes to change the color of the video. Our method is simple and intuitive, enabling compelling time-varying recoloring results. Compared to existing methods, our approach is more efficient in palette extraction and can effectively capture the dominant colors of the video. Extensive experiments demonstrate the effectiveness of our method.

IEEE Transactions on Image ProcessingVol. 34
Qinghai University (CN), Tsinghua University (CN)
Openalex Percentile: Top 64%
Image Processing Techniques and Applications
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Fast Video Recoloring via Curve-based Palettes — Kun Xu, Zhicheng Huang, et al. · IEEE Transactions on Image Processing (2025) | TGRS Research Map | TGRS