On the influence of spectral calibration in hyperspectral image classification of leaves

被引：0

作者：

Castro, Rodrigo ^{[1
]}

Ochoa, Daniel ^{[1
]}

Criollo, Ronald ^{[1
]}

机构：

[1] ESPOL, Escuela Super Politecn Litoral, Campus Gustavo Galindo Km 30-5,Via Perimetral, Guayaquil, Ecuador

来源：

2017 CHILEAN CONFERENCE ON ELECTRICAL, ELECTRONICS ENGINEERING, INFORMATION AND COMMUNICATION TECHNOLOGIES (CHILECON) | 2017年

关键词：

Hyperspectral Imaging; Spectral Vegetation Indexes; Spectral Calibration; VEGETATION INDEXES; LOW-COST; PREDICTION; SYSTEM; WATER;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Automatic detection of physiological changes in leaves using close range hyperspectral data is becoming a new tool for biologists. Given the geometry of leaves, the reliability of spectral data strongly depends on a careful spectral and geometric calibrations. In this paper, we evaluate the effect of several calibration approaches on automatic classification of leave regions. For our experiments we employ an in-vivo leaf scanning system, then an unsupervised classifier is applied on each calibrated and non-calibrated image and the biological relevance of the output is evaluated using vegetative indexes. Finally, we make recommendations about how to improve the hyperspectral image processing pipeline for this kind of data sets.

引用

页数：6

共 50 条

[31] WaveFormer: Spectral-Spatial Wavelet Transformer for Hyperspectral Image Classification [J].

Ahmad, Muhammad ;

Ghous, Usman ;

Usama, Muhammad ;

Mazzara, Manuel .

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2024, 21 :1-5

[32] Adversarially Robust Hyperspectral Image Classification via Random Spectral Sampling and Spectral Shape Encoding [J].

Park, Sungjune ;

Lee, Hong Joo ;

Ro, Yong Man .

IEEE ACCESS, 2021, 9 :66791-66804

[33] MSTNet: A Multilevel Spectral-Spatial Transformer Network for Hyperspectral Image Classification [J].

Yu, Haoyang ;

Xu, Zhen ;

Zheng, Ke ;

Hong, Danfeng ;

Yang, Hao ;

Song, Meiping .

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60

[34] Spatial-Spectral Joint Classification of Hyperspectral Image With Locality and Edge Preserving [J].

Zhang, Hui ;

Liu, Wanjun ;

Lv, Huanhuan .

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2020, 13 (13) :2240-2250

[35] Spectral Partitioning Residual Network With Spatial Attention Mechanism for Hyperspectral Image Classification [J].

Zhang, Xiangrong ;

Shang, Shouwang ;

Tang, Xu ;

Feng, Jie ;

Jiao, Licheng .

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60

[36] Cooperative Spectral-Spatial Attention Dense Network for Hyperspectral Image Classification [J].

Dong, Zhimin ;

Cai, Yaoming ;

Cai, Zhihua ;

Liu, Xiaobo ;

Yang, Zhaoyu ;

Zhuge, Mingchen .

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2021, 18 (05) :866-870

[37] Kmeans-CM Algorithm With Spectral Angle Mapper for Hyperspectral Image Classification [J].

Wei, Lin ;

Ma, Huiyun ;

Yin, Yuping ;

Geng, Chao .

IEEE ACCESS, 2023, 11 :26566-26576

[38] Class-Oriented Spectral Partitioning for Remotely Sensed Hyperspectral Image Classification [J].

Liu, Yi ;

Li, Jun ;

Du, Peijun ;

Plaza, Antonio ;

Jia, Xiuping ;

Zhang, Xinchang .

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2017, 10 (02) :691-711

[39] Feature Extraction Using Multidimensional Spectral Regression Whitening for Hyperspectral Image Classification [J].

Tu, Bing ;

Ren, Qi ;

Zhou, Chengle ;

Chen, Siyuan ;

He, Wei .

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2021, 14 :8326-8340

[40] Cross-Attention Spectral-Spatial Network for Hyperspectral Image Classification [J].

Yang, Kai ;

Sun, Hao ;

Zou, Chunbo ;

Lu, Xiaoqiang .

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60

← 1 2 3 4 5 →