Abstract
The energy budget is limited in remote applications of Wireless Vision Sensor Network (WVSN). It imposes strict constraints on both the processing energy consumption and transmission energy consumption of the Vision Sensor Nodes (VSN). Transmitting the raw images to the Central Base Station (CBS) consume substantial portion from the energy budget of each of the VSN. The consequence of greater transmission energy consumption due to transmitting raw images is the reduced lifetime of the VSN. Image compression standards effectively reduce the transmission energy consumption by compressing the images. But the computational complexity of a compression method has also a significant effect on the energy budget and lifetime of each of the VSN. This paper investigates the impact of the computational complexity and communication energy consumption of three chosen compression methods on the lifetime of the VSN. Both statistically generated images and the real captured images are used for evaluating the energy consumption of the three chosen image compression methods. We have determined the improvement in the lifetime of the VSN based on the computational complexity and compression ratio of the three selected binary image coding methods.