mlsanityData to 7 Oct 2026

Guided Colorization Using Mono-Color Image Pairs

arXiv 2108.07471 ↗First posted 17 Aug 2021cs.CVcited by 1

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Abstract (arXiv)

Compared to color images captured by conventional RGB cameras, monochrome images usually have better signal-to-noise ratio (SNR) and richer textures due to its higher quantum efficiency. It is thus natural to apply a mono-color dual-camera system to restore color images with higher visual quality. In this paper, we propose a mono-color image enhancement algorithm that colorizes the monochrome image with the color one. Based on the assumption that adjacent structures with similar luminance values are likely to have similar colors, we first perform dense scribbling to assign colors to the monochrome pixels through block matching. Two types of outliers, including occlusion and color ambiguity, are detected and removed from the initial scribbles. We also introduce a sampling strategy to accelerate the scribbling process. Then, the dense scribbles are propagated to the entire image. To alleviate incorrect color propagation in the regions that have no color hints at all, we generate extra color seeds based on the existed scribbles to guide the propagation process. Experimental results show that, our algorithm can efficiently restore color images with higher SNR and richer details from the mono-color image pairs, and achieves good performance in solving the color bleeding problem.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 19 of its 78 references that are in the map. First posted on arXiv 17 Aug 2021.

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19 of 78 references.

References · 19

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  12. 2019Deep Exemplar-based Video Colorizationcited by 75
7 more
  1. 2016Deep Colorizationcited by 70
  2. 2018Fast End-to-End Trainable Guided Filtercited by 50
  3. 2016Video Propagation Networkscited by 45
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