Histogram and entropy oriented image coding for clustered wireless multimedia sensor networks (WMSNS) (Apr, 10.1007/s11042-022-13060-2, 2022)

Recently, the advent of Wireless Multimedia Sensor Networks (WMSNs) has given birth to different applications. Some of the applications those required the deployment of low cost multimedia sensors include traffic monitoring, visual surveillance, habitat monitoring, environment monitoring etc. Unlike the traditional Wireless Sensor Networks (WSNs) which aims at the maximization of network lifetime, the main objective of WMSNs is an optimized multimedia data delivery along with the minimization of energy consumption. The major aspect in the WMSNs is the removal of redundant data before its transmission to sink. Even though several standard image compression techniques (ex. JPEG and MPEG) are there in the existence, they are not suitable for resource constrained WMSNs. To solve these problems, in this paper, we propose a new and simple image coding and transmission method. In this method, the histogram based representation is employed to encode the image while entropy based assessment is employed for data redundancy. Initially the network is clustered into several clusters and the nodes with rich resources are chosen as Cluster Heads (CH). After receiving the image data from sensor nodes, the CH performs joint entropy evaluation and discovers the uncorrelated data and then forwards to sink. Furthermore, the CH also determines the uncorrelated camera sensor nodes and allows only those nodes to report. An extensive simulation experiments are conducted over the developed approach and the performance is measured through several performance metrics like Energy Consumption, Peak Signal to Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM). © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.