A factor graph evidence combining approach to image defogging

作者：

Highlights：

• A novel factor graph approach for inference tasks provided in a layered arrangement.

• Factor nodes are rearranged into junction trees by using Delaunay triangulation and simplexes.

• The method is general in nature and therefore applicable to a variety of problems that have interdependent variables.

• The method is demonstrated to be comparable or better than existing methods for image defogging.

摘要

•A novel factor graph approach for inference tasks provided in a layered arrangement.•Factor nodes are rearranged into junction trees by using Delaunay triangulation and simplexes.•The method is general in nature and therefore applicable to a variety of problems that have interdependent variables.•The method is demonstrated to be comparable or better than existing methods for image defogging.

论文关键词：Factor graphs,Evidence combining,Simplicial spanning tree,Procrustes transformation,Maximum a-posteriori inference,Image defogging

论文评审过程：Received 14 February 2017, Revised 25 January 2018, Accepted 24 April 2018, Available online 5 May 2018, Version of Record 15 June 2018.

论文官网地址：https://doi.org/10.1016/j.patcog.2018.04.023