No-reference image quality assessment plays an important role in various applications. This book provides a thorough exploration of NR-IQA, including an introduction to fundamental concepts and principles, representative traditional and DNN-based approaches, as well as some human-inspired NR-IQA models that draw on insights from human visual perception to further improve the performance of NR-IQA models. The main goal of this book is to offer a comprehensive resource for researchers interested in this field, to provide valuable insights and guidance in understanding and applying these innovative no-reference image quality assessment techniques.