A Multi-Dimensional Correlation Matrix Feature Extraction Technique for Hyperspectral Images
碩士 === 國立臺北科技大學 === 電機工程系研究所 === 95 === A novel study of feature extraction technique for hyperspectral images of remote sensing is proposed. The method is based on the greedy modular eigenspace (GME) scheme, which was designed to extract the simplest and the most efficient feature modules for high-...
Main Authors: | Yun-Ming Liu, 劉原銘 |
---|---|
Other Authors: | Jyh-Perng Fang |
Format: | Others |
Language: | zh-TW |
Published: |
2007
|
Online Access: | http://ndltd.ncl.edu.tw/handle/38z36g |
Similar Items
-
Hyperspectral Image Classification with Multi-Scale Feature Extraction
by: Bing Tu, et al.
Published: (2019-03-01) -
Hyperspectral image classification based on multi-layer feature extraction
by: Qi Yongfeng, et al.
Published: (2018-01-01) -
Hyperspectral Image Classification via Multi-Feature-Based Correlation Adaptive Representation
by: Guichi Liu, et al.
Published: (2021-03-01) -
Multi-scale guided feature extraction and classification algorithm for hyperspectral images
by: Shiqi Huang, et al.
Published: (2021-09-01) -
High Dimensional Feature for Hyperspectral Image Classification
by: Wang Cailing, et al.
Published: (2018-01-01)