%0 Journal Article
%T Efficient Image Transmission over WVSNs Using Two-Measurement Matrix Based CS with Enhanced OMP
%A Hemalatha Rajendran
%A Radha Sankararajan
%A Jalbin Justus
%J International Journal of Distributed Sensor Networks
%D 2014
%I Hindawi Publishing Corporation
%R 10.1155/2014/386982
%X WVSN is a collective network of motes containing visual sensors. The nodes in the network are capable of acquiring, compressing, and transmitting successive images to the sink. To increase the lifetime of such network, it is essential to reduce the amount of dataflow across the network without losing the integrity. This paper proposes a CS-based image transmission system to reduce the number of measurements required to represent the image. It utilizes a two-measurement matrix-based CS. TMM with CS leads to 2.8% to 6.7% and 0.67% to 7.9% reduction in the number of measurements compared to one MM-based CS while using DCT and binary DCT, respectively. Similarly, TMM with NUS CS leads to 5% to 40% (DCT) and 1.4% to 20% (binDCT) reduction in the number of measurements than one-measurement matrix-based NUS CS. An Enhanced Orthogonal Matching Pursuit algorithm is also proposed, which produces nearly 2% to 26% better recovery rate with the same number of measurements than the conventional OMP algorithm. Reduced measurements and better recovery rate achieved will enhance the lifetime of the WVSN, with considerable image quality. Rate distortion analysis of the proposed methodology is also done. 1. Introduction WVSNs are networks of wirelessly interconnected devices equipped with camera, enabling the retrieval of video and audio streams, still images, and scalar sensor data. They have tiny visual sensor nodes called camera nodes as shown in Figure 1, which integrate the image sensor, embedded processor, and wireless transceiver [1]. WVSNs have large volume of data to be processed and stored which increases the complexity of the system. With the advancement in the image sensor technology, WVSNs can be used for more complex multimedia applications like border surveillance using visual monitoring, tracking rare animal species, controlling the vehicle traffic on highways, and railways and environmental monitoring [1¨C3]. However, they are energized by small batteries with a short span of lifetime. Replacing or recharging of the battery is also extremely difficult. With reduced lifetime of the batteries image transfer application in WVSNs has the limitations such as reduced bandwidth, reduced on board memory, and limited computational capability. Hence, it is essential to aim at diminishing the amount of data to be processed and the level of computations involved. Figure 1: Visual sensor network architecture [ 1]. WVSNs are in need of a compression process with acceptable compression rate, low computational complexity, low power consumption, and low dynamic memory
%U http://www.hindawi.com/journals/ijdsn/2014/386982/