基于高光谱跨场景迁移学习的集成对齐子空间自适应算法

doi:10.12305/j.issn.1001-506X.2025.02.04

Abstract

Abstract:

To solve the cross-scene classification problem, an aligned subspace adaptive ensemble learning algorithm combining ensemble learning and domain adaptive is proposed. Firstly, multiple random sampling is performed on the original data to solve the sample imbalance problem. Then, the source and target domains are geometrically and statistically aligned to construct a common subspace. Finally, the target scene data are classified, and the final classification labels are derived by calculating the classification results of multiple times while preserving the valid information. The proposed aligned subspace adaptive ensemble learning algorithm can solve the uncertainty and randomness of projection during the transfer process. Experimental results carried out on two datasets show that the proposed algorithm has a significant improvement in accuracy compared to traditional machine learning and domain adaptive methods.

Key words: cross-scene classification, domain adaptive, ensemble learning, hyperspectral, transfer learning

CLC Number:

TP751

Yijia SONG, Haiyan WANG, Wei FENG, Yinghui QUAN. An aligned subspace adaptive ensemble algorithm based on hyperspectral cross-scene transfer learning[J]. Systems Engineering and Electronics, 2025, 47(2): 369-375.

Figures/Tables 10

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References 30

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序号	名称	样本数量
序号	名称	休斯顿2013	休斯顿2018
1	健康草坪	198	1 858
2	受压草坪	190	6 068
3	树木	188	3 331
4	水域	182	24
5	居民楼	196	6 480
6	非居民楼建筑	191	37 778
7	道路	193	7 695
8	总数	1 338	63 234

序号	名称	样本数量
序号	名称	休斯顿2013	休斯顿2018
1	密集城市肌理	1 262	288
2	矿产开发地点	204	67
3	非灌溉工地	614	542
4	果树	150	79
5	橄榄树	1 768	1 401
6	针叶林	361	500
7	茂密叶绿植被	5 035	3 793
8	稀疏叶绿植被	6 374	2 803
9	植被稀疏地区	1 754	404
10	岩石和沙地	492	487
11	水域	1 612	1 393
12	沿海水域	398	451
13	总数	20 024	12 208

序号	分类算法
序号	SVM	KNN	TCA	CORAL	DCA	ASAEL
1	0	0.16	86.02	74.92	95.43	100.00
2	9.67	10.12	87.83	1.53	76.68	96.78
3	83.10	76.55	43.11	93.76	38.67	38.19
4	62.50	79.17	100.00	0	0	0
5	2.98	20.69	66.36	41.31	40.14	74.92
6	44.00	24.34	15.46	28.88	61.11	73.59
7	0.04	1.78	34.29	8.54	78.99	92.35

序号	分类算法
序号	SVM	KNN	TCA	CORAL	DCA	ASAEL
1	0	17.01	27.78	4.17	5.21	3.13
2	0	89.55	86.57	83.58	0	0
3	0	42.44	64.02	6.09	38.93	45.94
4	0	27.85	45.57	3.80	0	0
5	0	1.00	61.17	1.07	0	0
6	0	45.60	22.00	14.2	23.80	2.40
7	0	78.33	61.67	83.55	66.57	75.90
8	100	29.65	47.48	63.22	69.71	63.18
9	0	43.07	8.17	8.91	97.03	99.50
10	0	23.20	5.75	3.70	18.07	17.25
11	0	100.00	100.00	100.00	100.00	100.00
12	0	100.00	97.34	100.00	100.00	100.00

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An aligned subspace adaptive ensemble algorithm based on hyperspectral cross-scene transfer learning

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