本书采用非物理模型方法和物理模型方法，详细阐述了“图像质量提升”这一科学概念。在面向专家同行的技术性论文和面向大众读者的科普性文章中，展现了不同的传播学特征，从而确立了水下图像质量提升的多维角度，并揭示了在实际应用中数据采集、实验设置、模型优化、自适应调参等多个环节之间的复杂关系。这些内容不仅展示了水下图像增强与复原方法的最新进展，还强调了在不同大众需求下的科学传播策略，有助于学术研究与实际应用的紧密结合。此外，该书通过详细的实验验证，强调了水下图像增强研究在揭示水下环境光学特性、丰富图像增强算法体系、肯定新技术实际应用影响等方面的重要学术意义。因此，无论是研究对象、研究方法，还是研究意义，本研究都具备一定的创新价值。

Chapter 1 Underwater Image Enhancement via Minimal Color Loss and Locally Adaptive Contrast Enhancement
1.1 Introduction
1.2 Background
1.3 Methodology
1.3.1 Motivation
1.3.2 Locally Adaptive Color Correction
1.3.3 Locally Adaptive Contrast Enhancement
1.4 Experiment and Analysis
1.4.1 Parameter Sensitivity Analysis
1.4.2 Comprehensive Comparisons on the UIEB Dataset
1.4.3 Comparisons of Detail Enhancement
1.4.4 Comparisons of Runtime
1.4.5 Ablation Study
1.5 Conclusion
Chapter 2 Underwater Image Enhancement via Weighted Wavelet Visual Perception Fusion
2.1 Introduction
2.2 Related Work
2.3 Methodology
2.3.1 Motivation
2.3.2 Attenuation Map Guided Color Correction
2.3.3 Optimized Global Contrast
2.3.4 Optimized Local Contrast
2.3.5 Weighted Wavelet Fusion
2.4 Experiment and Analysis
2.4.1 Evaluation on the UIEB Dataset
2.4.2 Evaluation of Detail Enhancement
2.4.3 Ablation Study
2.5 Conclusion
Chapter 3 Underwater Image Enhancement by Attenuated Color Channel Correction and Detail Preserved Contrast Enhancement
3.1 Introduction
3.2 Related Work
3.3 Methodology
3.3.1 Attenuated Color Channel Correction
3.3.2 Global and Local Contrast Improvement
3.3.3 Multi-scale Fusion
3.3.4 Multi-scale Unsharp Masking
3.4 Experiment and Analysis
3.4.1 Comprehensive Evaluation on UIEB
3.4.2 Ablation Study
3.5 Conclusion
Chapter 4 Underwater Image Enhancement via Integrated RGB and LAB Color Models
4.1 Introduction
4.2 Related Work
4.3 Methodology
4.3.1 RGB Color Model-based Color Correction
4.3.2 LAB Color Model-based Local Contrast Enhancement and Gain Equalization
4.3.3 Sharpening of Texture Detail
4.4 Experiment and Analysis
4.4.1 Comprehensive Image Quality Comparisons on UIEB
4.4.2 Analysis of Runtime
4.4.3 Ablation Study
4.5 Conclusion
Chapter 5 Underwater Image Enhancement via Piecewise Color Correction and Dual Prior Optimized Contrast Enhancement
5.1 Introduction
5.2 Methodology
5.2.1 Piecewise Color Correction
5.2.2 Dual Prior Optimized Contrast Enhancement
5.3 Experiment and Analysis
5.3.1 Qualitative Evaluation
5.3.2 Quantitative Evaluation
5.3.3 Ablation Study
5.4 Conclusion
Chapter 6 Underwater Image Quality Improvement via Color, Detail, and Contrast Restoration
6.1 Introduction
6.2 Related Work
6.3 Methodology
6.3.1 Well-preserved Finding-driven Color Balance
6.3.2 Linear Saturation Transformation-based Discriminant Function-based Detail Restoration
6.3.3 Transmission Minimization-oriented Contrast Restoration
6.4 Experiment and Analysis
6.4.1 Parameter Sensitivity Analysis
6.4.2 Comprehensive Comparisons of Image Quality on UIEB
6.4.4 Ablation Study
6.4.5 Comparisons of Runtime
6.4.6 Generalization Performance of Our Method
6.5 Conclusion
Chapter 7 GIFM: An Image Restoration Method with Generalized Image Formation Model for Poor Visible Conditions
7.1 Introduction
7.2 Related Work
7.2.1 Single Image-based Methods
7.2.2 Multiple Images-based Methods
7.2.3 Deep Learning-based Methods
7.3 Methodology
7.3.1 A Novel Generalized Image Formation Model (GIFM)
7.3.2 Variation-based Alternating Decomposition
7.3.3 Adaptive Weighted Fusion-based Contrast and Brightness Improvement
7.4 Experiment and Analysis
7.4.1 Parameter Study
7.4.2 Validation on Underwater Hazy Images
7.5 Conclusion
Chapter 8 An Underwater Image Restoration Method Based on Adaptive Brightness Improvement and Local Image Descattering
8.1 Introduction
8.2 Methodology
8.2.1 Adaptive Brightness Improvement
8.2.2 Local Image Descattering
8.3 Experiment and Analysis
8.3.1 Quanlitative Comparison
8.3.2