ieee-standard-for-the-perceptual-quality-assessment-of-threedime.pdf

The hand is quicker than the eye. In many cases, so is digital video. Maintaining image quality in bandwidth - and memory - restricted environments is quickly becoming a reality as thriving research delves ever deeper into perceptual coding techniques, which discard superfluous data that humans cannot process or detect. Surveying the topic from a Human Visual System (HVS)-based approach, "Digital Video Image Quality and Perceptual Coding" outlines the principles, metrics, and standards

我们提出了一种基于结构相似性和视觉掩蔽的改进的客观图像质量评估方法，称为感知图像质量评估（PIQA）。 PIQA包含三个相似性度量：亮度比较度量，结构比较度量，与结构相似性（SSIM）相同的对比度比较度量及其变体。 首先，为了提高在模糊图像和嘈杂图像中区分结构信息的能力，我们使用改进的结构张量来修改结构比较度量，该结构张量在描述全局区域中的结构信息时更加有效。 其次，基于人类视觉系统（HVS）感知过程的感知特征，将对比度掩蔽和邻域掩蔽集成到对比度比较度量中。 最后，将三个度量汇总在一起以计算PIQA度量。 与多尺度SSIM（MS-SSIM），视觉信噪比（VSNR）和视觉信息保真度（VIF）标准等最新方法进行比较，仿真结果表明，我们的方法与HVS高度一致感知过程，并提供更好的性能。

The hand is quicker than the eye. In many cases, so is digital video. Maintaining image quality in bandwidth - and memory - restricted environments is quickly becoming a reality as thriving research delves ever deeper into perceptual coding techniques, which discard superfluous data that humans cannot process or detect. Surveying the topic from a Human Visual System (HVS)-based approach, "Digital Video Image Quality and Perceptual Coding" outlines the principles, metrics, and standards associated with p erceptual coding, as well as the latest techniques and applications. This book is divided broadly into three parts. First, it introduces the fundamental theory, concepts, principles, and techniques underlying the field, such as the basics of compression, HVS modeling, and coding artefacts associated with current well-known techniques. The next section focuses on picture quality assessment criteria; subjective and objective methods and metrics, including vision model based digital video impairment metrics; testing procedures; and international standards regarding image quality. Finally, practical applications come into focus, including digital image and video coder designs based on the HVS as well as post-filtering, restoration, error correction, and concealment techniques. The permeation of digital images and video throughout the world cannot be understated. Nor can the importance of preserving quality while using minimal storage space, and "Digital Video Image Quality and Perceptual Coding" provides the tools necessary to accomplish this goal.

图像哈希 感知哈希是多媒体文件的指纹，它是从其内容的各种功能派生而来的。 与依赖于输入中的小变化导致输出中的急剧变化的雪崩效应的密码散列函数不同，如果特征相似，则感知散列彼此“接近”。 与诸如MD5和SHA1的加密哈希函数相比，感知哈希是一个不同的概念。 使用加密哈希时，哈希值是随机的。 用于生成哈希的数据的行为类似于随机种子，因此相同的数据将生成相同的结果，但是不同的数据将生成不同的结果。 比较两个SHA1哈希值实际上仅告诉您两件事。 如果哈希不同，则数据也不同。 如果哈希相同，则数据可能相同。 相反，可以比较感知哈希值-使您感觉到两个数据集之间的相似性。 这段代码的启发/基于： 要求 PHP 7.1或更高版本 或扩展 （可选）安装扩展程序，以进行更快的指纹比较 安装 该软件包尚未达到稳定版本，在0.x版本之间可能会向后兼容。 如果您打算在生产中使用此版本，请确保将其锁定！

感知相似性指标和数据集 深度特征作为感知指标的不合理有效性（ ，（ ，（ ，（ ，（ 。 在 ，2018中。 快速开始 运行pip install lpips 。 下面的Python代码就是您所需要的。 import lpips loss_fn_alex = lpips . LPIPS ( net = 'alex' ) # best forward scores loss_fn_vgg = lpips . LPIPS ( net = 'vgg' ) # closer to "traditional" perceptual loss, when used for optimizat

该项目是ITU-R.BS.1387建议书的免费软件实现，该建议书描述了-音频质量的感知评估-（PEAQ）的算法。

FADE-图像去雾质量评价源码Referenceless Prediction of Perceptual Fog Density and Perceptual Image论文源码

The hand is quicker than the eye. In many cases, so is digital video. Maintaining image quality in bandwidth - and memory - restricted environments is quickly becoming a reality as thriving research delves ever deeper into perceptual coding techniques, which discard superfluous data that humans cannot process or detect. Surveying the topic from a Human Visual System (HVS)-based approach, "Digital Video Image Quality and Perceptual Coding" outlines the principles, metrics, and standards associated with perceptual coding, as well as the latest techniques and applications. This book is divided broadly into three parts. First, it introduces the fundamental theory, concepts, principles, and techniques underlying the field, such as the basics of compression, HVS modeling, and coding artefacts associated with current well-known techniques. The next section focuses on picture quality assessment criteria; subjective and objective methods and metrics, including vision model based digital video impairment metrics; testing procedures; and international standards regarding image quality. Finally, practical applications come into focus, including digital image and video coder designs based on the HVS as well as post-filtering, restoration, error correction, and concealment techniques. The permeation of digital images and video throughout the world cannot be understated. Nor can the importance of preserving quality while using minimal storage space, and "Digital Video Image Quality and Perceptual Coding" provides the tools necessary to accomplish this goal.