Hyperspectral image classification aided by LiDAR data

Zheng Deng; Genping Zhao; Shihui Zhao; Li Wang; Zhuowei Wang; Heng Wu; Lianglun Cheng

doi:10.1117/12.2680025

27 June 2023 Hyperspectral image classification aided by LiDAR data

Zheng Deng, Genping Zhao, Shihui Zhao, Li Wang, Zhuowei Wang, Heng Wu, Lianglun Cheng

Proceedings Volume 12705, Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022); 127051B (2023) https://doi.org/10.1117/12.2680025
Event: Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022), 2022, Nanjing, China

Abstract

Spectral variability and shadow effects can limit the hyperspectral image (HSI) classification performance. Compared with HSI, the LiDAR data is an excellent complement with its abundant elevation information. In this study, a procedure including pre-processing, deep residual network classification and post-processing is investigated for classification of HSI aided by the LiDAR data to release the problem of identifying shaded objects and spectral variability. Specifically, three aspects with respect to spectral band selection using Archetypal Analysis (AA), feature level fusion based classification by deploying a residual network associated approach and label correction utilizing the elevation information, are explored to realize more accurate classification. Experiments on three public multi-source (hyperspectral and LiDAR) remote sensing datasets show more promising classification can be achieved via fusion two-source of remote sensing data than that using only independent hyperspectral image. In particular, on the Houston 2017 dataset, OA and Kappa achieved significant gains of 2.47% and 2.79% respectively after incorporating LiDAR information. Moreover, the results demonstrate the elevation information used independently in the post-processing stage can help with effective refinement of classification results.

Citation Download Citation

Zheng Deng, Genping Zhao, Shihui Zhao, Li Wang, Zhuowei Wang, Heng Wu, and Lianglun Cheng "Hyperspectral image classification aided by LiDAR data", Proc. SPIE 12705, Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022), 127051B (27 June 2023); https://doi.org/10.1117/12.2680025

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available