中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 长春光学精密机械与物理研究所
  3. 中国科学院长春光学精密机械与物理研究所
Content-aware dynamic filter salient object detection network in multispectral polarimetric imagery

文献类型：期刊论文

作者S. N. Gao; X. B. Yang; L. Jiang; Z. M. Tu; M. Wu and Z. Q. Fu
刊名Optik
出版日期2022
卷号269页码:17
ISSN号0030-4026
DOI10.1016/j.ijleo.2022.169944
英文摘要Salient object detection (SOD) is widely applied in image segmentation, image fusion, and adaptive compression. However, the SOD of visible images in complex scenes remains a promi-nent problem due to the lack of low-level features. To solve this problem, a Content-aware Dy-namic Filter salient object detection Network using visible and polarized mask images is proposed. It can use the prior information on polarization dimension to guide the SOD of visual features. First, to extract information from the MSPI, a salient polarization mask M composed of three channels is generated. Secondly, deep fused features of the M and RGB images are generated by Encoder and DenseNet fusion structures with receptive fields. Finally, the fused features guide the decoder to generate saliency maps through the content-aware dynamic filtering model. The indexes of the salient object detection results given in this paper are superior to the state-of-the-art algorithms, especially for objects in dim, low contrast, or high transparency and other complex scenarios.
URL标识查看原文
语种英语
源URL[http://ir.ciomp.ac.cn/handle/181722/66488]  
专题中国科学院长春光学精密机械与物理研究所
推荐引用方式
GB/T 7714		 S. N. Gao,X. B. Yang,L. Jiang,et al. Content-aware dynamic filter salient object detection network in multispectral polarimetric imagery[J]. Optik,2022,269:17.
APA S. N. Gao,X. B. Yang,L. Jiang,Z. M. Tu,&M. Wu and Z. Q. Fu.(2022).Content-aware dynamic filter salient object detection network in multispectral polarimetric imagery.Optik,269,17.
MLA S. N. Gao,et al."Content-aware dynamic filter salient object detection network in multispectral polarimetric imagery".Optik 269(2022):17.

入库方式： OAI收割

来源：长春光学精密机械与物理研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。