Tomographic bioluminescence imaging suffers from poor imaging robustness, since it is severely affected by selection of regularization parameter (RP) and initialization for source distribution. In this paper, a global-inexact-Newton based reconstruction methodology, which is regularized by a dynamic sparse term, is demonstrated for in vivo tomographic imaging. The novel method can enhance higher imaging reliability and efficiency. Mouse experimental reconstructions were performed to validate the proposed method. These results demonstrate that the source distribution can be accurately located over a wide range of values of RP and iteration initializations. Moreover, the reconstruction efficiency was also studied.