GeoAI for spatial image processing
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Abstract
The development of digital image processing, as a subset of digital signal processing, depended upon the maturity of photography and image science, introduction of computers, discovery and advancement of digital recording devices, and the capture of digital images. In addition, government and industry applications in the Earth and medical sciences were paramount to the growth of the technology. From the early days when photography was first introduced to science to today, artificial intelligence and deep learning technologies have been intensively used to analyze imagery. Spatial image processing has experienced breakthroughs and evolutions. This chapter presents an overview of the history of image processing, GeoAI-based image processing applications, and the role of GeoAI in advancing image processing methods and research. We also discussed the remaining challenges to using GeoAI for image processing regarding training data annotation, the issues of scale, resolution, and change in space over time.
| Publication type | Book chapter |
|---|---|
| Publication Subtype | Book Chapter |
| Title | GeoAI for spatial image processing |
| DOI | 10.1201/9781003308423-5 |
| Edition | 1 |
| Year Published | 2023 |
| Language | English |
| Publisher | CRC Press |
| Contributing office(s) | Center for Geospatial Information Science (CEGIS) |
| Description | 24 p. |
| Larger Work Type | Book |
| Larger Work Subtype | Handbook |
| Larger Work Title | Handbook of Geospatial Artificial Intelligence |
| Google Analytic Metrics | Metrics page |