Decomposing Images into Layers with Advanced Color Blending


Yuki Koyama & Masataka Goto

National Institute of Advanced Industrial Science and Technology (AIST)

Our method can decompose the input image into semi-transparent layers associated with advanced color-blend modes such as hard-light and multiply.

Decomposed layers can be imported to Photoshop, After Effects, Krita, etc., and are useful to perform complex edits (e.g., lighting-aware hue change).

Video [2:39; no sound]

Abstract

Digital paintings are often created by compositing semi-transparent layers using various advanced color-blend modes, such as "color-burn," "multiply," and "screen," which can produce interesting non-linear color effects. We propose a method of decomposing an input image into layers with such advanced color blending. Unlike previous layer-decomposition methods, which typically support only linear color-blend modes, ours can handle any user-specified color-blend modes. To enable this, we generalize a previous color-unblending formulation, in which only a specific layering model was considered. We also introduce several techniques for adapting our generalized formulation to practical use, such as the post-processing for refining smoothness. Our method lets users explore possible decompositions to find the one that matches for their purposes by manipulating the target color-blend mode and desired color distribution for each layer, as well as the number of layers. Thus, the output of our method is a layered, easily editable image composition organized in a way that digital artists are familiar with. Our method is useful for remixing existing illustrations, flexibly editing single-layer paintings, and bringing physically painted media (e.g., oil paintings) into a digital workflow.

Web-App Demo

Publication

Yuki Koyama and Masataka Goto. 2018. Decomposing Images into Layers with Advanced Color Blending. Comput. Graph. Forum 37, 7, pp.397--407 (2018). (a.k.a. Proceedings of Pacific Graphics 2018)

DOI: 10.1111/cgf.13577

Download

Paper (authors' preprint)

PDF (14 MB)

Main video

MP4 (47 MB) YouTube

Talk slide

PDF (23 MB) SlideShare

High-res images & videos (for press etc.)

ZIP (103 MB)

Authors

Yuki Koyama

is a Researcher at National Institute of Advanced Industrial Science and Technology (AIST), Japan. His main research area is Computer Graphics and Human-Computer Interaction, specializing in computational design techniques.

Masataka Goto

is a Prime Senior Researcher at National Institute of Advanced Industrial Science and Technology (AIST), Japan. In 2016, as the Research Director he began a 5-year research project (JST OngaACCEL Project) on music technologies.