Geometric Algebra Applications in Geospatial Artificial Intelligence and Remote Sensing Image Processing

被引：46

作者：

Bhatti, Uzair Aslam ^{[1
]}

Yu, Zhaoyuan ^{[1
]}

Yuan, Linwang ^{[1
,2
]}

Zeeshan, Zeeshan ^{[3
]}

Nawaz, Saqib Ali ^{[4
]}

Bhatti, Mughair ^{[1
]}

Mehmood, Anum ^{[1
]}

Ul Ain, Qurat ^{[5
]}

Wen, Luo ^{[1
]}

机构：

[1] Nanjing Normal Univ, Sch Geog, Nanjing 210097, Peoples R China

[2] Nanjing Normal Univ, Key Lab Virtual Geog Environm, Minist Educ, Nanjing 210097, Peoples R China

[3] Kymeta Corp, Redmond, WA 98052 USA

[4] Hainan Univ, Coll Informat & Commun Engn, Haikou 570228, Hainan, Peoples R China

[5] Amazon Head Off, Seattle, WA 98109 USA

来源：

IEEE ACCESS | 2020年 / 8卷

基金：

中国国家自然科学基金;

关键词：

Geometric algebra; Clifford algebra; geometric algebra; computer vision; artificial intelligence; quaternions; SUPPORT VECTOR MACHINES; CLIFFORD-ALGEBRA; EDGE-DETECTION; SYSTEM; CLASSIFIER; REGRESSION;

D O I：

10.1109/ACCESS.2020.3018544

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

With the increasing demand for multidimensional data processing, Geometric algebra (GA) has attracted more and more attention in the field of geographical information systems. GA unifies and generalizes real numbers and complex, quaternion, and vector algebra, and converts complicated relations and operations into intuitive algebra independent of coordinate systems. It also provides a solution for solving multidimensional information processing with a high correlation among the dimensions and avoids the loss of information. Traditional methods of computer vision and artificial intelligence (AI) provide robust results in multidimensional processing after being combined with GA and give additional feature analysis facility to remote sensing images. In this paper, we provide a detailed review of GA in different fields of AI and computer vision regarding its applications and the current developments in geospatial research. We also discuss the Clifford-Fourier transform (CFT) and quaternions (sub-algebra of GA) because of their necessity in remote sensing image processing. We focus on how GA helps AI and solves classification problems, as well as improving these methods using geometric algebra processing. Finally, we discuss the issues, challenges, and future perspectives of GA with regards to possible research directions.

引用

页码：155783 / 155796

页数：14

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