1. A method, comprising: modeling a noise distribution based on image data by determining a noise standard deviation for sub-portions of voxels in the image data, wherein the sub-portions include outliers corresponding to non-homogeneous regions and inliers corresponding to homogenous regions; generating reduced noise image data based on the noise distribution by fitting various local structural models to the image data, selecting a model from the fitted models that is likely to remove noise from the image data while preserving the structure representing a scanned object or subject in the image data, and applying the selected model to the image data to remove noise; and generating enhanced image data based on the image data and the noise reduced image data by combining the image data and the noise reduced image data on a voxel-by-voxel basis based on a linear or non-linear mixing algorithm and predetermined image quality noise criteria, wherein an image quality of the enhanced image data is substantially similar to an image quality of higher dose image data.