Coherent diffractive imaging: a new statistically regularized amplitude constraint

Statistical information about measurement errors is incorporated in an algorithm that reconstructs the image of an object from x-ray diffraction data. The distribution function of measurement errors is included directly into reconstruction processes using a statistically based amplitude constraint. The algorithm is tested using simulated and experimental data and is shown to yield high-quality reconstructions in the presence of noise. This approach can be generalized to incorporate experimentally determined measurement error functions into image reconstruction algorithms.