期刊论文

Wei, Yantao

英文

Remote Sensing

2072-4292

2017

9

3

203

10.3390/rs9030203

National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61502195, 61472155]; Macau Science and Technology Development Fund [FDCT/016/2015/A1]; Research Committee at University of Macau [MYRG2014-00003-FST, YRG2016-00123-FST]; National Science & Technology Supporting Program during the Twelfth Five-year Plan Period - Ministry of Science and Technology of China [2015BAK27B02]; Self-Determined Research Funds of CCNUFrom the Colleges' Basic Research and Operation of MOEunder Grants [CCNU14A05023, CCNU16A05022, CCNU15A02020]; Postdoctoral Science Foundation of ChinaChina Postdoctoral Science Foundation [2015M582223]

本校为第一且通讯机构

This paper presents a hierarchical deep framework called Spectral-Spatial Response (SSR) to jointly learn spectral and spatial features of Hyperspectral Images (HSIs) by iteratively abstracting neighboring regions. SSR forms a deep architecture and is able to learn discriminative spectral-spatial features of the input HSI at different scales. It includes several existing spectral-spatial-based methods as special scenarios within a single unified framework. Based on SSR, we further propose the Subspace Learning-based Networks (SLN) as an example of SSR for HSI classification. In SLN, the joint ...