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2015 | OriginalPaper | Chapter

A Novel Edit Propagation Algorithm via \( L_0 \) Gradient Minimization

Authors : Zhenyuan Guo, Haoqian Wang, Kai Li, Yongbing Zhang, Xingzheng Wang, Qionghai Dai

Published in: Advances in Multimedia Information Processing -- PCM 2015

Publisher: Springer International Publishing

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Abstract

In this paper, we study how to perform edit propagation using \( L_0 \) gradient minimization. Existing propagation methods only take simple constraints into consideration and neglects image structure information. We propose a new optimization framework making use of \( L_0 \) gradient minimization, which can globally satisfy user-specified edits as well as tackle counts of non-zero gradients. In this process, a modified affinity matrix approximation method which efficiently reduces randomness is raised. We introduce a self-adaptive re-parameterization way to control the counts based on both original image and user inputs. Our approach is demonstrated by image recoloring and tonal values adjustments. Numerous experiments show that our method can significantly improve edit propagation via \( L_0 \) gradient minimization.

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Metadata
Title
A Novel Edit Propagation Algorithm via Gradient Minimization
Authors
Zhenyuan Guo
Haoqian Wang
Kai Li
Yongbing Zhang
Xingzheng Wang
Qionghai Dai
Copyright Year
2015
Book
Advances in Multimedia Information Processing -- PCM 2015

Print ISBN: 978-3-319-24074-9

Electronic ISBN: 978-3-319-24075-6

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-24075-6_39