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Image Processing Using Artificial Intelligence: Case Study on Classification of High-Dimensional Remotely Sensed Images
| Content Provider | Scilit |
|---|---|
| Author | Chutia, Dibyajyoti Chouhan, Avinash Nishant, Nilay Singh, P. Subhash Bhattacharyya, D. K. Raju, P. L. N. |
| Copyright Year | 2021 |
| Description | Recent advancement in artificial intelligence (AI) has created new vistas in various applications of image processing during the last two decades. Image-processing techniques have been adopted in many fields like electronics and telecommunications, medical science, remote sensing (RS), biotechnology, robotics, etc. The RS is one area where interpretation of image and associated processing techniques are very important in different stages of earth observation study. This area has drawn a lot of research interest in the advancement of image-processing techniques for long. The RS research focuses on the classification of satellite images, as the deliverables of classification process are the basic foundation for many application areas of natural resources and environment. During the last few decades, considerable amount of attempts has been made to examine the efficiency of conventional image processing techniques for enhancement of image quality as well as the classification accuracy of RS images. The current literature has shown significant potentials of machine learning (ML) approaches in object detection and pattern recognition with a high success rate. The classification process has raised considerable issues and interests when the characteristic of the landscape becomes too complex. The ML-based classification approaches have been found effective on many benchmark RS datasets. This chapter explores the issues and challenges of image-processing techniques in the classification of high-dimensional RS datasets. It discusses the potential of AI/ML-based approaches by showcasing a case study on the classification of Airborne ROSIS-3 hyperspectral sensor data. Finally, it provides the concluding remarks of the chapter and gives possible research directions for object detection and classification from very-high-resolution (VHR) RS dataset like unmanned aerial vehicle (UAV) imagery using deep learning (DL) techniques. Book Name: Artificial Intelligence |
| Related Links | https://api.taylorfrancis.com/content/chapters/edit/download?identifierName=doi&identifierValue=10.1201/9781003140351-6&type=chapterpdf |
| Ending Page | 49 |
| Page Count | 11 |
| Starting Page | 39 |
| DOI | 10.1201/9781003140351-6 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2021-10-05 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Artificial Intelligence Image Processing Techniques Classification of High Dimensional Study On Classification Object Detection Interest |
| Content Type | Text |
| Resource Type | Chapter |
