摄影图像和视频的去噪：基本原理、开放挑战和新趋势

This unique text/reference presents a detailed review of noise removal for photographs and video. An international selection of expert contributors provide their insights into the fundamental challenges that remain in the field of denoising, examining how to properly model noise in real scenarios, how to tailor denoising algorithms to these models, and how to evaluate the results in a way that is consistent with perceived image quality. The book offers comprehensive coverage from problem formulation to the evaluation of denoising methods, from historical perspectives to state-of-the-art algorithms, and from fast real-time techniques that can be implemented in-camera to powerful and computationally intensive methods for off-line processing. Topics and features: describes the basic methods for the analysis of signal-dependent and correlated noise, and the key concepts underlying sparsity-based image denoising algorithms; reviews the most successful variational approaches for image reconstruction, and introduces convolutional neural network-based denoising methods; provides an overview of the use of Gaussian priors for patch-based image denoising, and examines the potential of internal denoising; discusses selection and estimation strategies for patch-based video denoising, and explores how noise enters the imaging pipeline; surveys the properties of real camera noise, and outlines a fast approximation of nonlocal means filtering; proposes routes to improving denoising results via indirectly denoising a transform of the image, considering the right noise model and taking into account the perceived quality of the outputs.

This concise and clearly written volume will be of great value to researchers and professionals working in image processing and computer vision. The book will also serve as an accessible reference for advanced undergraduate and graduate students in computer science, applied mathematics, and related fields.

"The relentless quest for higher image resolution, greater ISO sensitivity, faster frame rates and smaller imaging sensors in digital imaging and videography has demanded unprecedented innovation and improvement in noise reduction technologies. This book provides a comprehensive treatment of all aspects of image noise including noise modelling, state of the art noise reduction technologies and visual perception and quantitative evaluation of noise.”

Geoff Woolfe, Former President of The Society for Imaging Science and Technology.

"This book on denoising of photographic images and video is the most comprehensive and up-to-date account of this deep and classic problem of image processing. The progress on its solution is being spectacular. This volume therefore is a must read for all engineers and researchers concerned with image and video quality." Jean-Michel Morel, Professor at Ecole Normale Supérieure de Cachan, France.

这本书/参考书详细介绍了照片和视频中噪声去除的技术。来自世界各地的专家贡献者提供了他们对这个领域基本挑战的见解，探讨了如何在真实场景中正确建模噪声、如何将去噪算法定制到这些模型，并以与感知图像质量一致的方式评估结果。

本书从问题表述到去噪方法评价提供全面覆盖，从历史角度到最先进的算法，以及从可直接在相机上实现的快速实时技术到强大的计算密集型处理方法。 章节和特点：描述了分析信号依赖性和相关噪声的基本方法和基于稀疏性的图像去噪算法的关键概念；回顾最成功的变分方法用于图像重建，并介绍卷积神经网络为基础的去噪方法；概述使用高斯先验进行基于patch的图像去噪的应用，探讨内部去噪的可能性；讨论基于patch的视频去噪选择与估计策略，探索噪声如何进入成像管道；调查实际相机噪声的性质，并提出非局部均值过滤快速近似的轮廓；通过间接对图像变换去噪以改进去噪结果，考虑正确的噪声模型并考虑到输出质量。

这本书将为在图像处理和计算机视觉领域的研究人员和技术人员提供极大的价值。对于计算机科学、应用数学等相关领域中高级本科生和研究生而言，本书也将是一个易于访问的参考书。

数字成像与视频中的图像分辨率、感光度更快帧率以及较小成像传感器的需求，一直在推动去噪技术方面前所未有的创新和改进。这本书提供了所有关于噪声建模、最先进的去噪技术以及视觉感知和噪声量化评估的所有方面的一揽子完整的治疗。

Geoff Woolfe, The Society for Imaging Science and Technology的前主席。

摄影图像和视频中去噪这一深刻且经典的图像处理问题的最新全面记录，是这个难题的解决方案进展令人惊叹。因此，这本书对所有关心图像和视频质量的所有工程师和技术人员而言都是必读之物。

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