Computational Intelligence Methods for Super-Resolution in Image Processing Applications

Computational Intelligence Methods for Super-Resolution in Image Processing Applications

This book explores the application of deep learning techniques within a particularly difficult computational type of computer vision (CV) problem ─ super-resolution (SR). The authors present and discuss ways to apply computational intelligence (CI) methods to SR. The volume also explores the possibi...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Deshpande, Anand (Editor), Estrela, Vania V. (Editor), Razmjooy, Navid (Editor)
Format: Electronic eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2021.
Edition:1st ed. 2021.
Subjects:
Computational intelligence.
Biomedical engineering.
Nanotechnology.
Optical data processing.
Artificial intelligence.
Online Access:Full text (Wentworth users only)
Table of Contents:
  • Part I. A Panorama of Computational Intelligence in Super-Resolution Imaging
  • Chapter 1. Introduction to Computational Intelligence and Super-Resolution
  • Chapter 2. Review on Fuzzy Logic Systems with Super-Resolved Imaging and Metaheuristics for Medical Applications
  • Chapter 3. Super-Resolution with Deep Learning Techniques-A Review
  • Chapter 4. A Comprehensive Review of CAD Systems in Ultrasound and Elastography for Breast Cancer Diagnosis
  • Part II. State-of-the-Art Computational Intelligence in Super-Resolution Imaging
  • Chapter 5. Pictorial Image Synthesis from Text and Its Super-Resolution using Generative Adversarial Networks
  • Chapter 6. Analysis of Lossy and Lossless Compression Algorithms for Computed Tomography Medical Images Based on Bat and Simulated Annealing Optimization Techniques
  • Chapter 7. Super resolution-based Human-Computer Interaction System for Speech and Hearing Impaired using Real-Time Hand Gesture Recognition System
  • Chapter 8. Lossy Compression of Noisy Images Using Autoencoders for Computer Vision Applications
  • Chapter 9. Recognition of Handwritten Nandinagari Palm Leaf Manuscript Tex
  • Chapter 10. Deep Image Prior and Structural Variation Based Super-Resolution Network for Fluorescein Fundus Angiography Images
  • Chapter 11. Lightweight Spatial Geometric Models Assisting Shape Description and Retrieval and Relative Global Optimum Based Measure for Fusion
  • Chapter 12. Dual-Tree Complex Wavelet Transform and Deep CNN-based Super-Resolution for Video Inpainting with Application to Object Removal and Error Concealment
  • Chapter 13. Super-Resolution Imaging and Intelligent solution for Classification, Monitoring and Diagnosis of Alzheimer's Disease
  • Chapter 14. Image Enhancement using Non-Local Prior and Gradient Residual Minimization for Improved Visualization of Deep Underwater Image
  • Chapter 15. Relative Global Optimum Based Measure for Fusion Technique in Shearlet Transform Domain for Prognosis of Alzheimer Disease.

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