Pixel Binning in Digital Radiography Imaging

In digital radiography imaging, pixel binning is an effective way to reduce the amount of image data for transmission or storage, and is particularly effective for application to dynamic digital radiography detectors for fluoroscopic imaging. Traditional pixel binning methods can be described as the process of downsampling an image that has been processed with a moving average (MA) filter for anti-aliasing purposes. In this paper, the performance of pixel binning is analyzed in terms of the noise power spectrum (NPS), modulation transfer function (MTF), and detective quantum efficiency (DQE) based on theoretical derivations. The performance of the pixel binning method is analyzed by performing theoretical analysis and Monte Carlo simulations through parametric modeling for NPS and MTF. Using x-ray images acquired from direct and indirect conversion detectors, the performances of pixel binning are compared and analyzed. Through theoretical analysis and experiments, we demonstrate that the pixel binning method can approach the DQE performance achieved by downsampling after applying an anti-aliasing filter. However, we found that using a better anti-aliasing filter instead of MA can improve DQE performance, especially for direct conversion detectors.