Interactive Image Colorization Using Laplacian Coordinates

Image colorization is a modern topic in computer vision which aims at manually adding colors to grayscale images. Techniques devoted to colorize images differ in many fundamental aspects as they often require an excessive number of image scribbles to reach pleasant colorizations. In fact, spreading lots of scribbles in the whole image consists of a laborious task that demands great efforts from users to accurately set appropriate colors to the image. In this work we present a new framework that only requires a small amount of image annotations to perform the colorization. The proposed framework combines the high-adherence on image contours of the Laplacian Coordinates segmentation approach with a fast color matching scheme to propagate colors to image partitions. User can locally manipulate colored regions so as to further improve the segmentation and thus the colorization result. We attest the effectiveness of our approach through a set of practical applications and comparisons against existing colorization techniques.