Abstract: Wildlife monitoring is the basis of effective protection, sustainable use and scientific management of wildlife resources. In order to obtain image information of wildlife monitoring remotely and in real time, wireless multimedia sensor network was introduced to the field of wildlife monitoring. The key of acquiring and transmitting image through wireless multimedia sensor network is image compression. However, the traditional image compression algorithm is not suitable for wireless multimedia sensor network owing to its computational complexity, long compression time, large volume of compression data and other shortcomings. The compressed sensing theory put forward in recent years, has achieved a low-speed sampling signal coding and accurate reconstruction and greatly reduces the computational complexity and also provides a new way of thinking to improve the conventional image compression algorithm. This study demonstrates the advantages of using wireless multimedia sensor network to monitor wildlife and expounds the basic principle of compressed sensing theory and its application in image compression. On this basis, the study also discusses the possibility that image compression algorithm based on compressed sensing theory is applied to wireless multimedia sensor network. Last but not the least, it is confirmed that image compression algorithm based on compressed sensing theory is suitable for wireless multimedia sensor network by doing the simulation experiments in MATLAB.