To enhance intensity of Cerenkov fluorescence and promote clinical transformation of Cerenkov luminescence imaging (CLI) technology, we propose an enhanced Cerenkov luminescence imaging (ECLI) technology by utilizing radioluminescence microparticles (RLMPs) in previous study, and the technolgoy can enhance the intensity of Cerenkov fluorescence effectively. To extend the application of ECLI technology to the field of three-dimension imaging, we propose a novel single-view enhanced Cerenkov luminescence tomography (ECLT) reconstruction method. In this method, single-view data acquisition is used, and sparse Bayesian learning (SBL) reconstruction algorithm combined with the strategy of iterative-shrinking permissible region is adopted to solve the inverse problem. Non-homogeneous cylinder simulation and physical phantom experiments are designed and conducted to verify the accuracy and stability of the proposed method. The results indicate that the proposed method can improve the reconstruction accuracy and speed, and the method has good stability and can effectively mitigate the ill-posedness of the inverse problem.