For the ill-posed linear inverse problem, we propose a hybrid regularization model, which possesses the characters of Tikhonov regularization and TV regularization to some extent. Through transformation, the hybrid regularization is reformulated as an equivalent minimization problem. To solve the minimization problem, we present two modified iterative shrinkage-thresholding algorithms (MISTA) based on the fast iterative shrinkage-thresholding algorithm (FISTA) and the iterative shrinkage-thresholding algorithm (ISTA). The numerical experiments are performed to show the effectiveness and superiority of the regularization model and the presented algorithms.