The imaging sensors are able to provide intuitive visual information for quick recognition and decision. However, imaging sensors usually generate vast amount of data. Therefore, processing and coding of image data collected in a sensor network for the purpose of energy efficient transmission poses a significant technical challenge. In particular, multiple sensors may be collecting similar visual information simultaneously. We propose in this paper a novel collaborative image coding and transmission scheme to minimize the energy for data transmission. First, we apply a shape matching method to coarsely register images to find out maximal overlap to exploit the spatial correlation between images acquired from neighboring sensors. For a given image sequence, we transmit background image only once. A lightweight and efficient background subtraction method is employed to detect targets. Only the regions of target and their spatial locations are transmitted to the monitoring center. The whole image can then be reconstructed by fusing the background and the target images as well as their spatial locations. Experimental results show that the energy for image transmission can indeed be greatly reduced with collaborative image coding and transmission.