Reconstructing High Resolution Image from Overlapped Low Resolution Projection Data

The authors present two novel algorithms of reconstructing high resolution image from overlapped parallel projection data with low resolution. One is called virtual detector algorithm, and the other is direct reconstruction algorithm. Both of the algorithms are developed from the interpolative algebraic reconstruction technique (IART) contributed by E.J. Mazur and R. Gordon. The main assumption in the paper is that the linear array of detectors can shift along the line of the array with a step which is less than the width of the detectors, and the overlapped projection data can be collected by overlapped sampling. The simulation results show that high resolution images can be reconstructed by means of both algorithms from the overlapped projection data. Moreover, the quality of the image reconstructed by the virtual detector algorithm from the overlapped low resolution projection data is almost as good as that of the image reconstructed directly from the high projection data. Although the resolution of the image reconstructed by direct reconstruction algorithm is slight lower than that of the image reconstructed by the virtual detector algorithm, the direct reconstruction algorithm adapts to any kind of overlapped projection data.