HyperSpectral Salient Object Detection Dataset (HS-SOD)

This is a hyperspectral salient object detection dataset with a collection of 60 hyperspectral images with their respective ground-truth binary images and representative rendered colour images (sRGB). We took several aspects in consideration during the data collection such as variation in object size, number of objects, foreground-background contrast, object position on the image, and etc. We also prepared ground truth binary images for each hyperspectral data, where salient objects are labelled on the images.
Creator :
Geoinformation Service Research Team, Digital Architecture Research Center, National Institute of Advanced Industrial Science and Technology
License :
First Publication Date : Tue, 05 Jun 2018 JST
Citation :
  • Nevrez Imamoglu, Yu Oishi, Xiaoqiang Zhang, Guanqun Ding, Yuming Fang, Toru Kouyama, Ryosuke Nakamura, “Hyperspectral Image Dataset for Benchmarking on Salient Object Detection”, 10th International Conference on Quality of Multimedia Experience (QoMEX), Sardinia, Italy, May 29 - June 1, 2018. (paper)
Tue, 24 Aug 2021 11:24:33 JST