Video-based sensor networks can be used to improve environment surveillance, health care and emergency response. Many sensor network scenarios require multiple high quality video streams that share limited wireless bandwidth. At the same time, the lifetime of wireless video sensors are constrained by the capacity of their batteries. Media scaling may extend battery life by reducing the video data rate while still maintaining visual quality, but comes at the expense of additional compression time. This thesis studies the effects of media scaling on video sensor energy consumption by: measuring the energy consumption on the different components of the video sensor; building a energy consumption model with several adjustable parameters to analyze the performance of a video sensor; exploring the trade-offs between the video quality and the energy consumption for a video sensor; and, finally, building a working video sensor to validate the accuracy of the model. The results show that the model is an accurate representation of the power usage of an actual video sensor. In addition, media scaling is often an effective way to reduce energy consumption in a video sensor.