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SIGGRAPH2023顶会

Image vectorization and editing via linear gradient layer decomposition

Zheng-Jun Du, Liang-Fu Kang, Jianchao Tan, Yotam I. Gingold, Kun Xu

2023年份
18被引次数
16顶会引用

摘要

Fig. 1. Given the input image (1st column) and a segmentation mask (2nd column), we can decompose the image into several linear gradient layers to be saved in vector graphics (3rd column). Then we can perform recoloring (4th column) or object remove-insert-replace edits using these linear gradient layers in illustrator software (5th column). Image designed by Altagracia Art on Shutterstock.com.

A key advantage of vector graphics over raster graphics is their editability. For example, linear gradients define a spatially varying color fill with a few intuitive parameters, which are ubiquitously supported in standard vector graphics formats and libraries. By layering regions filled with linear gradients, complex appearances can be created. We propose an automatic method to convert a raster image into layered regions of linear gradients. Given an input raster image segmented into regions, our approach decomposes the resulting regions into opaque and semi-transparent linear gradient fills. Our approach is fully automatic (e.g., users do not identify a background as in previous approaches) and exhaustively considers all possible decompositions that satisfy perceptual cues. Experiments on a variety of images demonstrate that our method is robust and effective.

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