Computed Tomography (CT) scanners evolved from simple parallel-beam geometry into more complex fan-beam geometry. The rebinning mechanism to convert fan-beam projections to parallel-beam projections is one of the methods simplifying the reconstruction of the CT image. Various interpolation methods result in different numerical presentations and noisy textures in the reconstructed CT images. This paper evaluates three interpolation methods, linear, frequency domain and higher order in rebinning fan-beam data into parallel-beam data in the framework of the FBP algorithm in parallel-beam CTs. The high-contrast spatial resolution, modulation transfer function (MTF), and noise are used to quantify the image quality. The noise is expressed as the noise power spectrum (NPS) and noise variance of the reconstructed image containing only Poisson distributed noise. Our results show that the higher order interpolation, cubic-spline, is the most helpful to improve the image quality in rebinning. We further demonstrate that the rebinning data gives more satisfactory results for assessment of noise variance in comparison with the fan-beam data.