X-ray Luminescence Computed Tomography (XLCT), a novel imaging technique which can obtain anatomical structure and functional information simultaneously, has an important application prospect in early tumor detection and radiotherapy. But due to the less measurement and complex imaging model, the tomography reconstruction always is a challenging problem. This paper presents a gradient algorithm based on Non-monotone Barzilai-Borwein(NBBG) to obtain the optimal solution of the objective. In each iteration, a spectral gradient-projection method approximately was minimized as a least-squares problem with an explicit L1-regularized constraint. The Barzilai-Borwein was employed to get the appropriate updating direction, further to improve the convergence speed of the proposed method. In addition, anonmonotone line search strategy was applied to build the optimal step length, which guarantees global convergence. The combination of nonmonotone line Barzilai-Borwein step length search strategy with spectral projected gradient method not only can ensure the global convergence, but also can reduce the computational cost of selecting exact step-size. From numerical simulation experiments and the physical experiment, the Location Errors(LE) of single target reconstruction based on NBBG are 0.68 and 0.94 mm respectively. Compared with Split Augmented Lagrangian Shrinkage Algorithm(SALSA), NBBG can obtain better results in terms of LE, robustness and efficiency.