A Novel Compression Method for Transmitting Multimedia Data in Wireless Multimedia Sensor Networks

Abstract

This paper discusses various compression methods used in wireless sensor networks. Compressed sensing is the emerging signal processing tool that makes the transmission of data easy via low-data rate links. In the wireless sensor network applications, a group of sensors is used to sense any events and make decisions, and the collaborated information sensed by different tiny sensing devices are used to give the decisions about the occurrence of the particular events. According to the different applications and data types, the quality of service parameters and designing parameters for nodes are different. For dealing with low bandwidth in a sensor network, it is most important to reduce the transmitted data bits between sensor nodes or from nodes to sink. In the case of multimedia data such as image signals, the compression is beneficial for the reduction of these bits because fewer bits required less transmission energy. In some situations of the multimedia sensor network, some loss is accepted without affecting the too much quality of results. Data collected by nodes are spatially correlated with each other, so the image samples collected over time by the nodes are also correlated with each other. If only some samples are transmitted, then these samples are sufficient to give the knowledge about the suspected object inside the monitoring area, so the transformation-based compression technique is the good solution for the compression in the case of the multimedia sensor network. In this paper, a Hadamard transform-based compression technique is discussed for image compression with the consideration of different designing parameters of an image signal. In that manner, this work helps us to select the transform and source coding schemes for the compression of image data inside the wireless multimedia sensor network.