Digital Image Enhancement and Reconstruction
- 1st Edition - October 6, 2022
- Imprint: Academic Press
- Editors: Shyam Singh Rajput, Nafis Uddin Khan, Amit Kumar Singh, Karm Veer Arya
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 9 8 3 7 0 - 9
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 9 8 5 7 8 - 9
Digital Image Enhancement and Reconstruction: Techniques and Applications explores different concepts and techniques used for the enhancement as well as reconstruction of low-qu… Read more
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Request a sales quoteDigital Image Enhancement and Reconstruction: Techniques and Applications explores different concepts and techniques used for the enhancement as well as reconstruction of low-quality images. Most real-life applications require good quality images to gain maximum performance, however, the quality of the images captured in real-world scenarios is often very unsatisfactory. Most commonly, images are noisy, blurry, hazy, tiny, and hence need to pass through image enhancement and/or reconstruction algorithms before they can be processed by image analysis applications. This book comprehensively explores application-specific enhancement and reconstruction techniques including satellite image enhancement, face hallucination, low-resolution face recognition, medical image enhancement and reconstruction, reconstruction of underwater images, text image enhancement, biometrics, etc. Chapters will present a detailed discussion of the challenges faced in handling each particular kind of image, analysis of the best available solutions, and an exploration of applications and future directions. The book provides readers with a deep dive into denoising, dehazing, super-resolution, and use of soft computing across a range of engineering applications.
- Presents comprehensive coverage of digital image enhancement and reconstruction techniques
- Explores applications across range of fields, including intelligent surveillance systems, human-computer interaction, healthcare, agriculture, biometrics, modelling
- Explores different challenges and issues related to the implementation of various techniques for different types of images, including denoising, dehazing, super-resolution, and use of soft computing
Researchers, professionals, and graduate students in computer science & engineering; electrical engineering
- Cover image
- Title page
- Table of Contents
- Copyright
- List of contributors
- Preface
- Acknowledgments
- Chapter 1: Video enhancement and super-resolution
- Abstract
- Acknowledgement
- 1.1. Introduction
- 1.2. Recent related work
- 1.3. Analysis of low-quality video IE model based on DL algorithm
- 1.4. Results and discussion
- 1.5. Conclusion
- References
- Chapter 2: On estimating uncertainty of fingerprint enhancement models
- Abstract
- 2.1. Introduction
- 2.2. Related work
- 2.3. Model uncertainty estimation
- 2.4. Data uncertainty estimation
- 2.5. Experimental evaluation
- 2.6. Results and analysis
- 2.7. Conclusion
- References
- Chapter 3: Hardware and software based methods for underwater image enhancement and restoration
- Abstract
- 3.1. Introduction
- 3.2. Literature survey
- 3.3. Research gaps
- 3.4. Conclusion and future scope
- References
- Chapter 4: Denoising and enhancement of medical images by statistically modeling wavelet coefficients
- Abstract
- 4.1. Introduction
- 4.2. Literature survey
- 4.3. Background and basic principles
- 4.4. Methodology
- 4.5. Simulation results
- 4.6. Conclusion
- References
- Chapter 5: Medical image denoising using convolutional neural networks
- Abstract
- 5.1. Introduction
- 5.2. Different medical imaging modalities
- 5.3. Convolutional neural networks
- 5.4. Review on existing CNN denoisers
- 5.5. Result and discussion
- 5.6. Challenges of CNN's denoisers
- 5.7. Conclusion
- References
- Chapter 6: Multimodal learning of social image representation
- Abstract
- 6.1. Introduction
- 6.2. Representation learning methods of social media images
- 6.3. Conclusion
- References
- Chapter 7: Underwater image enhancement: past, present, and future
- Abstract
- List of abbreviations
- 7.1. Introduction
- 7.2. Underwater environment
- 7.3. Underwater image enhancement methods
- 7.4. Underwater image datasets
- 7.5. Underwater image quality assessment
- 7.6. Challenges and future recommendations
- 7.7. Conclusion
- References
- Chapter 8: A comparative analysis of image restoration techniques
- Abstract
- 8.1. Introduction
- 8.2. Reasons for degradation in image
- 8.3. Image restoration techniques
- 8.4. Performance analysis of image restoration
- 8.5. Performance analysis
- 8.6. Conclusion
- References
- Chapter 9: Comprehensive survey of face super-resolution techniques
- Abstract
- 9.1. Introduction
- 9.2. Face image degradation model
- 9.3. Classification of face hallucination methods
- 9.4. Assessment criteria of face super-resolution algorithm
- 9.5. Issues and challenges
- 9.6. Conclusion
- References
- Chapter 10: Fusion-based backlit image enhancement and analysis of results using contrast measure and SSIM
- Abstract
- 10.1. Introduction
- 10.2. Basic HVS characteristics
- 10.3. Methodology
- 10.4. Result discussion
- 10.5. Summary
- References
- Chapter 11: Recent techniques for hyperspectral image enhancement
- Abstract
- 11.1. Introduction
- 11.2. The major objective of hyperspectral image enhancement
- 11.3. Recent techniques in hyperspectral image enhancement by compressing the image
- 11.4. Advantages of hyperspectral imaging over multispectral imaging
- 11.5. Application of hyperspectral image
- 11.6. Conclusion
- References
- Chapter 12: Classification of COVID-19 and non-COVID-19 lung computed tomography images using machine learning
- Abstract
- Acknowledgements
- 12.1. Introduction
- 12.2. Methodology
- 12.3. Results
- 12.4. Discussions
- 12.5. Limitations and future improvements
- 12.6. Conclusion
- References
- Chapter 13: Brain tumor image segmentation using K-means and fuzzy C-means clustering
- Abstract
- 13.1. Introduction
- 13.2. Brain tumor extraction using image segmentation
- 13.3. Review on K-means clustering
- 13.4. Review on fuzzy C-means clustering
- 13.5. Performance analysis and assessment
- 13.6. Observations and discussions
- 13.7. Conclusions
- References
- Chapter 14: Multimodality medical image fusion in shearlet domain
- Abstract
- 14.1. Introduction
- 14.2. Multimodality medical image fusion
- 14.3. Proposed methodology
- 14.4. Results and discussion
- 14.5. Conclusions
- References
- Chapter 15: IIITM Faces: an Indian face image database
- Abstract
- Acknowledgements
- 15.1. Introduction
- 15.2. Related work
- 15.3. Methodology
- 15.4. Experimental setup
- 15.5. Results
- 15.6. Conclusions
- References
- Index
- Edition: 1
- Published: October 6, 2022
- No. of pages (Paperback): 378
- No. of pages (eBook): 378
- Imprint: Academic Press
- Language: English
- Paperback ISBN: 9780323983709
- eBook ISBN: 9780323985789
SR
Shyam Singh Rajput
Dr. Rajput earned his PhD in Computer Science & Engineering from ABV-Indian Institute of Information Technology & Management (ABV-IIITM), Gwalior, India. He has more than four years of teaching experience with undergraduate and postgraduate classes. Presently he is working as an assistant professor in CSE Department, National Institute of Technology Patna, India. His current research interests include image processing and computer vision. He has published more than 25 journal and conference articles in the areas of image processing, biometrics, wireless ad hoc networks, and information security.
Affiliations and expertise
Assistant Professor, CSE Department, National Institute of Technology, Patna, Bihar, IndiaNK
Nafis Uddin Khan
Dr. Khan received his Ph.D. in Computer Science & Engineering from ABV- Indian Institute of Information Technology and Management, Gwalior. He is currently Assistant Professor in the Department of ECE, Jaypee University of Information Technology, Solan. His areas of research interest include digital signal and image processing, adaptive image processing and fuzzy based applications in image processing. He has more than 5 years of teaching experience of undergraduate and post graduate level Engineering courses. He has published 14 research papers in various journals and conferences of national and international repute.
Affiliations and expertise
Assistant Professor, Department of ECE, Jaypee University of Information Technology, Solan, IndiaAS
Amit Kumar Singh
Amit Kumar Singh is an associate professor at the Department of Computer Science and Engineering, National Institute of Technology Patna, Bihar, India. Dr. Singh have been recognized as "World Ranking of Top 2% Scientists" in the area of “Biomedical Research" (for Year 2019) and "Artificial Intelligence & Image Processing" (for the Year 2020 and 2021) according to the survey given by Stanford University, USA. Currently, Dr. Singh is the Associate Editor of IEEE Trans. on Multimedia, ACM Trans. Multimedia Comput. Commun. Appl., IEEE Trans. Computat. Social Syst., IEEE Trans. Ind. Informat., IEEE J. Biomed. Heal. Informatics Etc. His research interests include multimedia data hiding, image processing, compression, biometrics, Cryptography.
Affiliations and expertise
Associate Professor, Department of Computer Science and Engineering, National Institute of Technology Patna, Bihar, IndiaKA
Karm Veer Arya
Dr. Arya received his PhD in Computer Science & Engineering from the Indian Institute of Technology (I.I.T. Kanpur), Kanpur, India. He is now Professor of Computer Science at ABV-Indian Institute of Information Technology & Management (IIITM), Gwalior. He also served as Dean of Postgraduate Studies & Research at AKTU Lucknow. He has more than 29 years of experience teach undergraduate and postgraduate students and has guided more than 100 PhD and MTech dissertations. He has published 11 book chapters and more than 150 journal and conference papers in the fields of image processing, biometrics, and information security. Dr. Arya is co-author of the book, Security in Mobile Ad-hoc Networks, and editor of two books, Emerging Wireless Communication and Biometric Computing. Dr. Arya is on the editorial board of numerous international journals and a member of the organizing committee and program committees for various national and international conferences and workshops. He a is Senior Member of IEEE, Fellow of IETE, Fellow of IE, and Life Member of ISTE.
Affiliations and expertise
Professor of Computer Science, ABV Indian Institute of Information Technology and Management, Gwalior, IndiaRead Digital Image Enhancement and Reconstruction on ScienceDirect