Scalable image segmentation via decoupled sub-graph compression
作者：
Highlights：
• A scalable graph compression algorithm for image segmentation proposed.
• The input image is represented by a region graph model.
• Texton dictionaries capture the local texture features in decoupled sub-graphs.
• A graph compression algorithm reduces the graph size and segments the image.
• Local graph decoupling and recoupling operations lead to an efficient method.
摘要
•A scalable graph compression algorithm for image segmentation proposed.•The input image is represented by a region graph model.•Texton dictionaries capture the local texture features in decoupled sub-graphs.•A graph compression algorithm reduces the graph size and segments the image.•Local graph decoupling and recoupling operations lead to an efficient method.
论文关键词：Segmentation,Graph compression,Decoupling,Scalability
论文评审过程：Received 17 January 2017, Revised 21 August 2017, Accepted 30 November 2017, Available online 6 December 2017, Version of Record 5 February 2018.
论文官网地址：https://doi.org/10.1016/j.patcog.2017.11.028
