Network lifetime maximization is a critical issue in wireless sensor networks since each sensor has a limited energy supply. In contrast with conventional sensor networks, video sensor nodes compress the video before transmission. The encoding process demands a high power consumption, and thus raises a great challenge to the maintenance of a long network lifetime. In this paper, we examine a strategy for maximizing the network lifetime in wireless visual sensor networks by jointly optimizing the source rates, the encoding powers, and the routing scheme. Fully distributed algorithms are developed using the Lagrangian duality to solve the lifetime maximization problem. We also examine the relationship between the collected video quality and the maximal network lifetime. Through extensive numerical simulations, we demonstrate that the proposed algorithm can achieve a much longer network lifetime compared to the scheme optimized for the conventional wireless sensor networks.