视频传感器网络应用关键技术研究
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摘要
无线传感器网络作为物联网领域的基础技术之一，具有重要的研究价值和战略意义。随着技术的发展，无线传感器网络应用已经从传统的单一标量数据业务逐步转向复杂的语音、图像以及视频等多媒体数据业务。视频传感器网络作为无线多媒体传感器网络的一个典型应用实例，已逐渐成为国内外学术界关注和研究的热点，具有重要的理论和应用研究价值。
本文通过对视频传感器网络的研究分析，重点对视频传感器网络应用中涉及的三个方面的关键技术进行了详细的研究，包括能量有效的路由算法设计、定位与跟踪研究中信息准确性分析和视频与图像优化。以上研究在保证通信的准确性和有效性的前提下，为视频传感器网络的应用提供了创新性的理论指导。
在路由算法设计中，提出适用于视频传感器网络的一种能量有效的多路径路由算法。算法包括三部分：（1）建立从源节点到汇聚节点的梯度；（2）确定不相交多路径的规则；（3）设计工作路径选择的策略。在算法中通过限制梯度中相邻节点的最大值，有效地降低探测信息的转发次数；同时通过建立不相交多路径的路由算法，汇聚节点可以获得足够多不相交的多路径。整个多路径路由算法实施可以节约视频传感器网络能量，同时可以使网络从路由中断中快速地得到恢复。论文中对本文算法在平均能耗和建立路径延时方面与其它已有的相关算法相比较，并进行了性能评价。仿真结果表明，本文提出的路由算法能够有效提高视频传感器网络的能量效率。
定位与跟踪技术也是视频传感器网络应用研究中的一个重要内容。如何在能量和带宽有限的前提下提供准确的定位信息，对于视频传感器网络非常关键。本文针对定位与跟踪技术中信息的准确性进行了较深入的研究。在视频传感器网络中的一个关键问题是如何在有限的物理资源条件下（特别是在能源消耗方面）保证所需信息的准确性。通常的观点，更准确的信息可以通过使用更多的关联传感节点消耗更多的能源来实现。然而，我们的分析和仿真结果表明，在噪声存在的某些情况下，关联传感节点的增加也可能导致信息的准确性降低，当节点数量趋于无穷大时，信息准确性的增量接近为零。在本文中，我们基于信息准确性的定量定义，利用视频传感器网络中数据的空间相关性讨论了视频传感网络中信息准确性与关联传感节点的数量与位置的关系，并进行了仿真实验验证。
由于传感器网络中能量和带宽有限，必须对传送的视频进行有效的优化。视频传感网络通常采集和传送相当低分辨率的图像，在论文中我们提出采用图像分辨率增强技术，实现从低分辨率图像中恢复高分辨率图像，从而降低了视频传感器网络采集和传送图像的分辨率要求。增强图像分辨率的关键难题是保留图像中的边缘结构，本文提出了一种新的图像分辨率增强算法，即通过对未知像素附近的像素强度进行双边加权平均来估计它的强度。更确切地说，距离越近的相邻像素点拥有的权重也越大。在实验中我们通过与传统的基于边缘方向的图像插值算法进行比较，实验结果表明，本文设计的算法能获得较好的性能，同时该算法的计算复杂度较低，可以节约视频传感器网络上的能量耗费，具有较强的应用性。
综上所述，本文围绕视频传感器网络应用关键技术，通过对能量有效的路由算法设计、定位与跟踪的信息准确性分析和视频传感器网络中的图像优化这三方面的深入研究，进行了理论创新和算法设计并提供了相关实验数据。
As essential technology of the Internet of Things, Wireless Sensor Network (WSN)has important research value and strategic significance. Traditional wireless sensornetwork’s applications have been gradually exteneded from the traditional data services tovoice, images, video and other multimedia services. Video sensor network as a typicalapplication of Wireless Multimedia Sensor Networks (WMSN), has gradually becomeworldwide research interests, and has important theoretical and applied research value.
This paper, with study and analysis of Video Sensor Networks（VSN), focuses onresearch of the key technologies involved in video sensor network applications, such as thekey issues of energy efficient routing algorithm over VSN, precision study of positioningand tracking, as well as video and image optimization for VSN transmission. Under thepremise of ensuring the accuracy and effectiveness of the communication, the paperprovides a theoretical guidance for the video sensor network applications.
A novel energy-efficient multi-path routing algorithm for wireless sensor network isproposed in this paper. It consists of three elements:(i) gradients to disseminate data overmultiple paths from a source to a sink,(ii) rules to set up disjoint multiple paths, and (iii)policies to select the working path. By limiting the maximum number of the gradients, theexploratory data messages forwarded are decreased efficiently. By using the rules forsetting up disjoint multiple paths, the sink node can get a sufficient number of disjointmultiple paths, which enables our algorithm to recover from a routing failure quickly.Finally, we evaluate its performance and compare to other related algorithms fromperspectives of average dissipated energy and the delay to set up multiple paths.
Positioning and tracking technology is an important issue in the video sensor networkapplications, for the premise of limited energy and limited bandwidth, providing accuratelocation information is critical problem in video sensor networks. A key issue in wirelesssensor networks is to achieve required information accuracy under some physical resourceconstraints especially in terms of energy consumption. Intuitively, more accurateinformation can be achieved by using more jointly sensing nodes at the expense of moreenergy consumption. However, both our analytical and simulation results show thatinformation accuracy may also decrease as the number of jointly sensing nodes increases inthe presence of noise, and the increment of information accuracy reaches zero when thisnumber approaches infinity. In this paper, we discusse a model for information accuracy and the number and position of jointly sensing nodes in WSNs based on a quantitativedefinition of information accuracy by exploiting the spacial correlation between senseddata. The analytical results are validated by simulation.
Video sensor network usually uses fairly low-resolution images due to the limitedtransmission bandwidth in transmitting images. It is potential to enhance the capturedlow-resolution images using image resolution enhancement technique that is able toproduce a high-resolution image from its low-resolution counterpart.The key challenge ofimage resolution enhancement is to preserve the edge structure in images. In this paper, anew image resolution enhancement approach is proposed, in which the intensity of theunknown pixel is estimated by using a bilateral weighted average of its neighboring pixels,the neighboring pixels with nearer distance have larger contributions. Furthermore, theneighboring pixels belonging to direction with smaller variation have larger contributions.Experimental results are provided and summarized to show that the proposed approachoutperforms several conventional edge-directed image interpolation algorithms. The resultsshow that the proposed approach yields low computational complexity, which implies thatthe approach is more suitable for real-time applications.
In summary, this paper studied three key applied technologies in video sensornetworks, which include energy efficient routing algorithm design, positioning and trackinganalysis, video and image optimization. The analysis and simulation results show that theproposed algorithms are capable of improving the image quality and life-time of videosensor networks.
本文通过对视频传感器网络的研究分析，重点对视频传感器网络应用中涉及的三个方面的关键技术进行了详细的研究，包括能量有效的路由算法设计、定位与跟踪研究中信息准确性分析和视频与图像优化。以上研究在保证通信的准确性和有效性的前提下，为视频传感器网络的应用提供了创新性的理论指导。
在路由算法设计中，提出适用于视频传感器网络的一种能量有效的多路径路由算法。算法包括三部分：（1）建立从源节点到汇聚节点的梯度；（2）确定不相交多路径的规则；（3）设计工作路径选择的策略。在算法中通过限制梯度中相邻节点的最大值，有效地降低探测信息的转发次数；同时通过建立不相交多路径的路由算法，汇聚节点可以获得足够多不相交的多路径。整个多路径路由算法实施可以节约视频传感器网络能量，同时可以使网络从路由中断中快速地得到恢复。论文中对本文算法在平均能耗和建立路径延时方面与其它已有的相关算法相比较，并进行了性能评价。仿真结果表明，本文提出的路由算法能够有效提高视频传感器网络的能量效率。
定位与跟踪技术也是视频传感器网络应用研究中的一个重要内容。如何在能量和带宽有限的前提下提供准确的定位信息，对于视频传感器网络非常关键。本文针对定位与跟踪技术中信息的准确性进行了较深入的研究。在视频传感器网络中的一个关键问题是如何在有限的物理资源条件下（特别是在能源消耗方面）保证所需信息的准确性。通常的观点，更准确的信息可以通过使用更多的关联传感节点消耗更多的能源来实现。然而，我们的分析和仿真结果表明，在噪声存在的某些情况下，关联传感节点的增加也可能导致信息的准确性降低，当节点数量趋于无穷大时，信息准确性的增量接近为零。在本文中，我们基于信息准确性的定量定义，利用视频传感器网络中数据的空间相关性讨论了视频传感网络中信息准确性与关联传感节点的数量与位置的关系，并进行了仿真实验验证。
由于传感器网络中能量和带宽有限，必须对传送的视频进行有效的优化。视频传感网络通常采集和传送相当低分辨率的图像，在论文中我们提出采用图像分辨率增强技术，实现从低分辨率图像中恢复高分辨率图像，从而降低了视频传感器网络采集和传送图像的分辨率要求。增强图像分辨率的关键难题是保留图像中的边缘结构，本文提出了一种新的图像分辨率增强算法，即通过对未知像素附近的像素强度进行双边加权平均来估计它的强度。更确切地说，距离越近的相邻像素点拥有的权重也越大。在实验中我们通过与传统的基于边缘方向的图像插值算法进行比较，实验结果表明，本文设计的算法能获得较好的性能，同时该算法的计算复杂度较低，可以节约视频传感器网络上的能量耗费，具有较强的应用性。
综上所述，本文围绕视频传感器网络应用关键技术，通过对能量有效的路由算法设计、定位与跟踪的信息准确性分析和视频传感器网络中的图像优化这三方面的深入研究，进行了理论创新和算法设计并提供了相关实验数据。
As essential technology of the Internet of Things, Wireless Sensor Network (WSN)has important research value and strategic significance. Traditional wireless sensornetwork’s applications have been gradually exteneded from the traditional data services tovoice, images, video and other multimedia services. Video sensor network as a typicalapplication of Wireless Multimedia Sensor Networks (WMSN), has gradually becomeworldwide research interests, and has important theoretical and applied research value.
This paper, with study and analysis of Video Sensor Networks（VSN), focuses onresearch of the key technologies involved in video sensor network applications, such as thekey issues of energy efficient routing algorithm over VSN, precision study of positioningand tracking, as well as video and image optimization for VSN transmission. Under thepremise of ensuring the accuracy and effectiveness of the communication, the paperprovides a theoretical guidance for the video sensor network applications.
A novel energy-efficient multi-path routing algorithm for wireless sensor network isproposed in this paper. It consists of three elements:(i) gradients to disseminate data overmultiple paths from a source to a sink,(ii) rules to set up disjoint multiple paths, and (iii)policies to select the working path. By limiting the maximum number of the gradients, theexploratory data messages forwarded are decreased efficiently. By using the rules forsetting up disjoint multiple paths, the sink node can get a sufficient number of disjointmultiple paths, which enables our algorithm to recover from a routing failure quickly.Finally, we evaluate its performance and compare to other related algorithms fromperspectives of average dissipated energy and the delay to set up multiple paths.
Positioning and tracking technology is an important issue in the video sensor networkapplications, for the premise of limited energy and limited bandwidth, providing accuratelocation information is critical problem in video sensor networks. A key issue in wirelesssensor networks is to achieve required information accuracy under some physical resourceconstraints especially in terms of energy consumption. Intuitively, more accurateinformation can be achieved by using more jointly sensing nodes at the expense of moreenergy consumption. However, both our analytical and simulation results show thatinformation accuracy may also decrease as the number of jointly sensing nodes increases inthe presence of noise, and the increment of information accuracy reaches zero when thisnumber approaches infinity. In this paper, we discusse a model for information accuracy and the number and position of jointly sensing nodes in WSNs based on a quantitativedefinition of information accuracy by exploiting the spacial correlation between senseddata. The analytical results are validated by simulation.
Video sensor network usually uses fairly low-resolution images due to the limitedtransmission bandwidth in transmitting images. It is potential to enhance the capturedlow-resolution images using image resolution enhancement technique that is able toproduce a high-resolution image from its low-resolution counterpart.The key challenge ofimage resolution enhancement is to preserve the edge structure in images. In this paper, anew image resolution enhancement approach is proposed, in which the intensity of theunknown pixel is estimated by using a bilateral weighted average of its neighboring pixels,the neighboring pixels with nearer distance have larger contributions. Furthermore, theneighboring pixels belonging to direction with smaller variation have larger contributions.Experimental results are provided and summarized to show that the proposed approachoutperforms several conventional edge-directed image interpolation algorithms. The resultsshow that the proposed approach yields low computational complexity, which implies thatthe approach is more suitable for real-time applications.
In summary, this paper studied three key applied technologies in video sensornetworks, which include energy efficient routing algorithm design, positioning and trackinganalysis, video and image optimization. The analysis and simulation results show that theproposed algorithms are capable of improving the image quality and life-time of videosensor networks.
引文
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