Improving Image Clarity with Artificial Intelligence-Powered Super-Resolution Methods
- Title
- Improving Image Clarity with Artificial Intelligence-Powered Super-Resolution Methods
- Creator
- Malathy V.; Poornima M.; Varun V.L.; Venugopal P.; Acharjee P.B.; Krishnaveni S.
- Description
- Super-resolution has advanced significantly in the last 20years, particularly with the application of deep learning methods. One of the most important image processing methods for boosting an image's resolution in computer vision is image super-resolution besides providing an extensive overview of the most recent developments in artificial intelligence and deep learning for single-image super-resolution. This study delves into the subject of image enhancement by investigating sophisticated AI-based super-resolution techniques. High-quality photographs have become more and more in demand in a variety of industries recently, including medical imaging, satellite imaging, entertainment, and surveillance. Pixilation reduction and detail preservation are two areas where traditional image enhancing techniques fall short. Artificial intelligence has demonstrated amazing promise in addressing these issues, especially with regard to Deep Learning models. The applications, benefits, and difficulties of modern super-resolution techniques are thoroughly examined in this work. We also suggest new approaches and push the limits of image enhancement by experimenting with state-of-the-art artificial intelligence algorithms. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
- Source
- Smart Innovation, Systems and Technologies, Vol-390, pp. 127-140.
- Date
- 2024-01-01
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Subject
- Artificial intelligence; Deep learning; Image quality; Super resolution
- Coverage
- Malathy V., School of Engineering, SR University, Telangana, Warangal, India; Poornima M., Department of Mathematics, SJB Institute of Technology, Bengaluru, India; Varun V.L., Department of Mathematics, SJB Institute of Technology, Bengaluru, India; Venugopal P., Department of Mathematics, SJB Institute of Technology, Bengaluru, India; Acharjee P.B., Computer Science, CHRIST University Pune, Lavasa Campus, Lavasa, India; Krishnaveni S., Department of Management Studies, Adithya Institute of Technology, Coimbatore, Kovilpalayam, India
- Rights
- Restricted Access
- Relation
- ISSN: 21903018; ISBN: 978-981972715-5
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Malathy V.; Poornima M.; Varun V.L.; Venugopal P.; Acharjee P.B.; Krishnaveni S., “Improving Image Clarity with Artificial Intelligence-Powered Super-Resolution Methods,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/19304.