视觉传感器网络中基于散度模型的协作式图像压缩机制

Cooperation image compression algorithm using divergence model for visual sensor networks

结合视觉传感器网络的协同工作特性,提出一种基于散度模型的图像压缩机制。理论分析和实验结果表明,该压缩机制不仅可以减少图像数据量,而且由于压缩后每字节数据所含信息量由各簇内节点的二值量化像素均分,不会引起传输错误在图像中大面积扩散。相比于采用传统的图像压缩算法,随着平均分组丢失率的增高,接收图像峰值信噪比较高。

Utilizing the feature of cooperation in visual sensor networks,an image compression algorithm based on di-vergence model was proposed.Analysis and experimental results demonstrate that the compression scheme proposed can reduce the amount of image data effectively.And,due to the information represented by one byte is shared by several cluster nodes＇ bi-level pixels after compression,the degradation of received images is controlled.Comparing with the tra-ditional image compression algorithms,the quality of received image measured by PSNR is higher,as the average packet loss rate increases.