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Binary video codec for data reduction in wireless visual sensor networks

机译:用于无线视觉传感器网络的数据减少的二进制视频编解码器

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Wireless Visual Sensor Networks (WVSN) is formed by deploying many Visual Sensor Nodes (VSNs) in the field. Typical applications of WVSN include environmental monitoring, health care, industrial process monitoring, stadium/airports monitoring for security reasons and many more. The energy budget in the outdoor applications of WVSN is limited to the batteries and the frequent replacement of batteries is usually not desirable. So the processing as well as the communication energy consumption of the VSN needs to be optimized in such a way that the network remains functional for longer duration. The images captured by VSN contain huge amount of data and require efficient computational resources for processing the images and wide communication bandwidth for the transmission of the results. Image processing algorithms must be designed and developed in such a way that they are computationally less complex and must provide high compression rate. For some applications of WVSN, the captured images can be segmented into bi-level images and hence bi-level image coding methods will efficiently reduce the information amount in these segmented images. But the compression rate of the bi-level image coding methods is limited by the underlined compression algorithm. Hence there is a need for designing other intelligent and efficient algorithms which are computationally less complex and provide better compression rate than that of bi-level image coding methods. Change coding is one such algorithm which is computationally less complex (require only exclusive OR operations) and provide better compression efficiency compared to image coding but it is effective for applications having slight changes between adjacent frames of the video. The detection and coding of the Region of Interest (ROIs) in the change frame efficiently reduce the information amount in the change frame. But, if the number of objects in the change frames is higher than a certain level then the compression efficiency of both the change coding and ROI coding becomes worse than that of image coding. This paper explores the compression efficiency of the Binary Video Codec (BVC) for the data reduction in WVSN. We proposed to implement all the three compression techniques i.e. image coding, change coding and ROI coding at the VSN and then select the smallest bit stream among the results of the three compression techniques. In this way the compression performance of the BVC will never become worse than that of image coding. We concluded that the compression efficiency of BVC is always better than that of change coding and is always better than or equal that of ROI coding and image coding.
机译:无线视觉传感器网络(WVSN)是通过在该字段中部署许多可视传感器节点(VSN)来形成的。 WVSN的典型应用包括环境监测,医疗保健,工业过程监测,体育场/机场监测,供安全原因等等。 WVSN的户外应用中的能量预算仅限于电池,通常不希望频繁更换电池。因此,需要优化处理以及VSN的通信能量消耗,使得网络仍然具有更长的持续时间的方式。由VSN捕获的图像包含大量数据,并且需要有效的计算资源来处理用于传输结果的图像和宽通信带宽。必须以计算方式设计和开发图像处理算法,使得它们的计算方式更加复杂,并且必须提供高压缩率。对于WVSN的一些应用,捕获的图像可以被分段为双级图像,因此双级图像编码方法将有效地降低这些分段图像中的信息量。但是双级图像编码方法的压缩率受带下划线的压缩算法的限制。因此,需要设计其他智能和高效的算法,该智能和高效的算法,该智能和有效的算法复杂并提供比双级图像编码方法更好的压缩率。改变编码是一种这样的算法,该算法是计算不那么复杂的(仅需要独占或操作),并且与图像编码相比提供更好的压缩效率,但是对于在视频的相邻帧之间具有略微变化的应用是有效的。更改帧中的感兴趣区域(ROI)的检测和编码有效地降低了改变帧中的信息量。但是,如果改变帧中的对象数量高于一定级别,则改变编码和ROI编码的压缩效率变得比图像编码更差。本文探讨了二进制视频编解码器(BVC)的压缩效率,用于WVSN中的数据减少。我们建议实现所有三种压缩技术,即在VSN处编码图像编码,改变编码和ROI,然后在三个压缩技术的结果中选择最小的比特流。以这种方式,BVC的压缩性能永远不会变得比图像编码更糟糕。我们得出结论,BVC的压缩效率总是比变化编码更好,并且总是比ROI编码和图像编码更好或等于或等于。

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