发帖
雷达卡
摘要翻译：
光学相位调制条纹图通常用XxY像素和8比特/像素（或更高）的灰度级进行数字化。数字化的8位/像素是原始数据位，而不是香农信息位。在这里，我们表明，噪声条纹图存储的香农信息比数字化相机的容量少得多。这意味着高信噪比（S/N）相机可能会浪费大部分比特/像素去噪声。例如，人们不会使用智能手机相机进行高质量的相位测量，因为它们的（S/N）图像较低。然而，智能手机将高分辨率（1200万像素）图像数字化，正如我们在这里所展示的，图像的信息存储取决于它的带宽和它的（S/N）。测量信息的标准形式是香农熵H和香农容量定理(SCT)。根据SCT，低（S/N）图像可以用较大的条纹带宽进行补偿，以获得高信息的相位测量。因此，宽带条纹可以提供高质量的相位，尽管数字化低（S/N）条纹图像。大多数现实生活中的图像都是冗余的，它们具有像素值变化不大的平滑区域，数据压缩算法对图像传输/存储至关重要。利用Shannon容量定理对竞争图像压缩算法进行了度量。由于相位调制的相移条纹具有高度的相关性，因此，相移算法可以作为条纹数据压缩器。因此，PSA可以将大量相移条纹压缩到单个复值图像中。这在星载光学/雷达相位遥测中非常重要，在这种情况下，下行链路受到巨大距离和低功率下行链路的严重限制。也就是说，代替发送M个相移条纹，一个只发送相位解调信号作为压缩传感数据。
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英文标题：
《Shannon information storage in noisy phase-modulated fringes and
fringe-data compression by phase-shifting algorithms》
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作者：
Manuel Servin and Moises Padilla
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最新提交年份：
2017
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分类信息：
一级分类：Electrical Engineering and Systems Science 电气工程与系统科学
二级分类：Signal Processing 信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
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一级分类：Computer Science 计算机科学
二级分类：Information Theory 信息论
分类描述：Covers theoretical and experimental aspects of information theory and coding. Includes material in ACM Subject Class E.4 and intersects with H.1.1.
涵盖信息论和编码的理论和实验方面。包括ACM学科类E.4中的材料，并与H.1.1有交集。
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一级分类：Mathematics 数学
二级分类：Information Theory 信息论
分类描述：math.IT is an alias for cs.IT. Covers theoretical and experimental aspects of information theory and coding.
它是cs.it的别名。涵盖信息论和编码的理论和实验方面。
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一级分类：Physics 物理学
二级分类：Instrumentation and Detectors 仪器仪表和探测器
分类描述：Instrumentation and Detectors for research in natural science, including optical, molecular, atomic, nuclear and particle physics instrumentation and the associated electronics, services, infrastructure and control equipment.
用于自然科学研究的仪器和探测器，包括光学、分子、原子、核和粒子物理仪器和相关的电子学、服务、基础设施和控制设备。
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英文摘要：
Optical phase-modulated fringe-patterns are usually digitized with XxY pixels and 8 bits/pixel (or higher) gray-levels. The digitized 8 bits/pixel are raw-data bits, not Shannon information bits. Here we show that noisy fringe-patterns store much less Shannon information than the capacity of the digitizing camera. This means that high signal-to-noise ratio (S/N) cameras may waste to noise most bits/pixel. For example one would not use smartphone cameras for high quality phase-metrology, because of their lower (S/N) images. However smartphones digitize high-resolution (12 megapixel) images, and as we show here, the information storage of an image depends on its bandwidth and its (S/N). The standard formalism for measuring information are the Shannon-entropy H, and the Shannon capacity theorem (SCT). According to SCT, low (S/N) images may be compensated with a larger fringe-bandwidth to obtain high-information phase measurements. So broad bandwidth fringes may give high quality phase, in spite of digitizing low (S/N) fringe images. Most real-life images are redundant, they have smooth zones where the pixel-value do not change much, and data compression algorithms are paramount for image transmission/storage. Shannon's capacity theorem is used to gauge competing image compression algorithms. Here we show that phase-modulated phase-shifted fringes are highly correlated, and as a consequence, phase-shifting algorithms (PSAs) may be used as fringe-data compressors. Therefore a PSA may compress a large number of phase-shifted fringes into a single complex-valued image. This is important in spaceborne optical/RADAR phase-telemetry where downlink is severely limited by huge distance and low-power downlink. That is, instead of transmitting M phase-shifted fringes, one only transmit the phase-demodulated signal as compressed sensing data.
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PDF链接：
https://arxiv.org/pdf/1710.00623
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