Guided Colorization Using Mono-Color Image Pairs

Abstract

Compared to color images captured by conventional RGB cameras, monochrome images usually have better signal-tonoise 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.

Real‐time coloring method of laser surgery video based on generative adversarial network

“…Then, the algorithm automatically propagates the specified color in space and time to generate a fully colored image or sequence. [10][11][12] Levin et al 10 first proposed a scribble-based method. Recently, Kim et al 13 proposed an edge enhancement framework that can help edge correction in desired regions.…”