Compressive Video Sensing
Compressive Video Sensing
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DOI：
10.1109/msp.2016.2602099
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发表时间：
2017-01-01
影响因子：
14.9
通讯作者：
Wakin, Michael B.
中科院分区：
文献类型：
--
作者：
Baraniuk, Richard G.;Goldstein, Tom;Wakin, Michael B.
传统传感器的设计主要基于香农·奈奎斯特采样定理，该定理指出，如果采样率超过每秒 2 W 样本，则带宽 W Hz 的信号完全由其离散时间样本决定。对于离散时间信号，香农？奈奎斯特定理有一个非常简单的解释：数据样本的数量必须至少与被采样和恢复的信号的维数一样大。这一重要结果使得能够在离散时域中进行信号处理而不会丢失任何信息。然而，在越来越多的应用中，香农-奈奎斯特采样定理规定了不必要的且通常过高的采样率（请参阅“什么是视频信号的奈奎斯特速率？”）。作为一个激励人心的例子，现代相机中图像传感器硬件的高分辨率反映了捕获图像所需的大量数据。实际上，10 兆像素的相机可以对场景进行 1000 万次测量。然而，在采集之后，图像中的冗余几乎立即被利用来显着压缩所采集的数据，通常以 100:1 的压缩比进行可视化，对于检测和分类任务甚至更高的压缩比。这个例子表明传统相机的整体设计存在巨大的浪费。
The design of conventional sensors is based primarily on the Shannon?Nyquist sampling theorem, which states that a signal of bandwidth W Hz is fully determined by its discrete time samples provided the sampling rate exceeds 2 W samples per second. For discrete time signals, the Shannon?Nyquist theorem has a very simple interpretation: the number of data samples must be at least as large as the dimensionality of the signal being sampled and recovered. This important result enables signal processing in the discrete time domain without any loss of information. However, in an increasing number of applications, the Shannon-Nyquist sampling theorem dictates an unnecessary and often prohibitively high sampling rate (see "What Is the Nyquist Rate of a Video Signal?"). As a motivating example, the high resolution of the image sensor hardware in modern cameras reflects the large amount of data sensed to capture an image. A 10-megapixel camera, in effect, takes 10 million measurements of the scene. Yet, almost immediately after acquisition, redundancies in the image are exploited to compress the acquired data significantly, often at compression ratios of 100:1 for visualization and even higher for detection and classification tasks. This example suggests immense wastage in the overall design of conventional cameras.