Artificial Intelligent Algorithms for Image Dehazing and Non-Uniform Illumination Enhancement (Algorithms for Intelligent Systems)

✍ Scribed by Teena Sharma, Nishchal K. Verma

• Publisher: Springer
• Year: 2024
• Tongue: English
• Leaves: 158
• Edition: 2024
• Category: Library

✦ Synopsis

This book offers a detailed insight of artificial intelligence (AI) algorithms for image dehazing and non-uniform illumination enhancement. In this book, various image enhancement techniques under hazy and non-uniform illumination conditions are discussed. The book specifically provides a detail on how to approach image enhancement under different outdoor conditions using AI tools. The biggest benefit a reader would accrue is to get exposed to the various aspects one should take care of while working with digital images. The book also includes multiple inventions which were recently introduced by the authors for image enhancement and reviews the state of the art in respective subject matters.

✦ Table of Contents

Preface
Contents
About the Authors
Acronyms
List of Figures
List of Tables
1 Introduction
1.1 Image Enhancement
1.2 Image Matching
1.3 Image Dehazing
1.3.1 Atmospheric Scattering Model
1.3.2 Related Work
1.4 Non-uniform Illumination Enhancement
1.4.1 Retinex Theory
1.4.2 Related Work
1.5 Organization of the Book
References
2 Modified Transmission Map Estimation Function
2.1 Introduction
2.2 Methodology
2.2.1 Dark Channel
2.2.2 RGB to HSV Conversion
2.2.3 Modified Transmission Map Estimation Function
2.2.4 Atmospheric Light Estimation
2.2.5 Image Dehazing
2.3 Results and Discussions
2.3.1 Quantitative Comparison
2.3.2 Qualitative Comparison
2.4 Summary
References
3 Compact Single Image Dehazing Network
3.1 Introduction
3.2 Compact Single Image Dehazing Network
3.2.1 Hazy Input Features
3.2.2 Pre-activation
3.2.3 Convolutional Layers
3.2.4 Dehazed Image
3.3 Results and Discussions
3.3.1 Datasets
3.3.2 Network Parameters and Loss Function
3.3.3 Quantitative Comparison
3.3.4 Qualitative Comparison
3.3.5 Discussions
3.4 Summary
References
4 Z-Score Method
4.1 Introduction
4.2 Z-Score
4.3 Observations
4.4 Methodology
4.4.1 Single Image Dehazing
4.4.2 Non-uniform Illumination Enhancement
4.5 Results and Discussions
4.5.1 Quantitative Comparison
4.5.2 Qualitative Comparison
4.6 Summary
References
5 Image Dehazing Using Type-2 Fuzzy Approach
5.1 Introduction
5.2 Methodology
5.2.1 Minimum Channel
5.2.2 Type-2 MF Based Similarity Function Matrix
5.2.3 Depth Map and Scene Transmission
5.2.4 Global Atmospheric Light
5.2.5 Image Dehazing
5.3 Results and Discussions
5.3.1 Datasets
5.3.2 Performance Metrics
5.3.3 Quantitative Comparison
5.3.4 Qualitative Comparison
5.3.5 Detection Results
5.3.6 Variation in Patch Size
5.4 Summary
References
6 Adaptive Interval Type-2 Fuzzy Filter
6.1 Introduction
6.2 Methodology
6.2.1 Initial Coarse Illumination
6.2.2 Coarse Illumination Estimation Using Adaptive Interval Type-2 Fuzzy Filter
6.2.3 Reflectance
6.2.4 Image Composition and Denoising
6.3 Results and Discussions
6.3.1 Datasets and Performance Metrics
6.3.2 Quantitative Comparison
6.3.3 Qualitative Comparison
6.3.4 Variation in Patch Size
6.3.5 Type-1 Versus Type-2 Fuzzy Filter
6.4 Summary
References
7 Epilogue
7.1 Summary
7.2 Directions for Future Work