Multi-view image compression for visual sensor networks (VSNs)

This paper proposed an energy efficient multi-view visual processing scheme for the visual sensor networks (VSNs). The aim of this scheme is to reduce the energy consumption by reducing the amount of data need to be transmitted over the network. This is achieved by using two approaches. First, an image compression based on the Set Partitioning in Hierarchical Trees (SPIHT) [1] algorithm is implemented to compress the images before transmitting them over the network. Second, in cases where the Field-of-View (FoV) of different visual nodes is overlapped, the overlapping regions (redundant information) between the images will be identified at the host workstation to prevent them from being transmitted multiple times. This is to further reduce the data transmission. In this case, only one visual node is required to transmit the overlapping regions. The information obtained from the aforementioned visual node will be used to reconstruct the overlapping regions of other visual nodes at the host workstation. In other words, other visual nodes are only required to transmit the non-overlapping regions. Instead of transmitting the entire image over the network, only part of it will be transmitted. The simulations results show that our proposed scheme can reduce the data transmission for 50%. Furthermore, the quality of reconstructed images is acceptable and can be improved in further works.