This paper presents an image processing approach for correcting streaking artifacts in computed tomography (CT) images and compares it to physics based and composite approaches. In CT, there are two major sources for streaking artifacts: beam hardening and nonlinear partial volume averaging. The physics based approach uses a physical model for the beam hardening. Inaccuracy of the model and nonlinear partial volume averaging result in an incomplete correction of the artifacts by this approach. The proposed image processing approach identifies and corrects the artifacts using their frequency characteristics. It corrects the artifacts regardless of their source. The composite approach also utilizes the physical model for the beam hardening. Although correcting some of the artifacts, it is computationally more intense than the image processing approach. We illustrate the methods and compare their performance using a computer simulation and CT images of a phantom and a human brain. We show that the streaking artifacts resulting from nonlinear partial volume averaging which are not corrected by the physics based method are corrected by the image processing approach.