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Full Description
Digital 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.
Contents
1. Fundamentals of Image Enhancement: Techniques and applications
2. Fundamentals of Image Reconstruction: Concepts and Challenges
3. Soft Computing based Image Reconstruction and Enhancement
4. Image Enhancement for Underwater Images
5. Image Enhancement and Reconstruction for Smart Healthcare
6. Super-resolution of medical images - to come
7. Image Enhancement Techniques Used in Remote Sensing Satellite Imagery
8. Low Contrast Image Enhancement
9. Image Dehazing - to come
10. AI for Image enhancement and reconstruction - to come
11. Enhancement and Reconstruction of Night Vision Images
12. Color Image Reconstruction and Enhancement
13. Video Enhancement and Super-resolution
14. Biometric Image Enhancement and Reconstruction
15. 3D Image Reconstruction and Enhancement
16. Deep-Learning-Based Image Reconstruction and Enhancement
17. Image Reconstruction and Enhancement for Retinal Fundus Images
18. Image Enhancement in Agriculture
