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Author:

Pan, Jianjun (Pan, Jianjun.) | Cai, Yiheng (Cai, Yiheng.) | Tan, Meiling (Tan, Meiling.) | Xie, Jin (Xie, Jin.)

Indexed by:

EI SCIE

Abstract:

Hyperspectral image (HSI) classification is a procedure of interest in remote sensing. HSIs contain complex spectral and spatial information, so classification tasks remain difficult. Although current deep-learning models have made significant progress in HSI classification, dealing with spectral and spatial information still requires careful investigation. To better manage spectral and spatial information and improve classification accuracy, we introduce a multiscale residual weakly dense network with an attention mechanism. First, we designed two residual weakly dense (Res-WDens) branches to extract spectral and spatial feature information and then applied the Concat method to fuse the two kinds of information. We also designed a plug-and-play hybrid attention module to refine the fused information so the network could focus on the essential spectral and spatial features. Finally, considering the relevance of spectral and spatial information, a dual-channel multiscale feature extraction module was used to extract the spectral-spatial multiscale information of HSIs. The overall accuracies of our proposed method reached 99.76%, 99.97%, and 100% on three publicly available datasets. A series of experiments demonstrated that our method is comparable to current state-of-the-art methods. (C) 2022 Society of Photo-Optical Instrumentation Engineers (SPIE)

Keyword:

hyperspectral image classification attention mechanism residual network weakly dense network multiscale

Author Community:

  • [ 1 ] [Pan, Jianjun]Beijing Univ Technol, Sch Informat & Commun Engn, Beijing, Peoples R China
  • [ 2 ] [Cai, Yiheng]Beijing Univ Technol, Sch Informat & Commun Engn, Beijing, Peoples R China
  • [ 3 ] [Tan, Meiling]Beijing Univ Technol, Sch Informat & Commun Engn, Beijing, Peoples R China
  • [ 4 ] [Xie, Jin]Beijing Univ Technol, Sch Informat & Commun Engn, Beijing, Peoples R China

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Source :

JOURNAL OF APPLIED REMOTE SENSING

Year: 2022

Issue: 3

Volume: 16

1 . 7

JCR@2022

1 . 7 0 0

JCR@2022

ESI Discipline: GEOSCIENCES;

ESI HC Threshold:38

JCR Journal Grade:4

CAS Journal Grade:4

Cited Count:

WoS CC Cited Count: 1

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 6

Affiliated Colleges:

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