High-resolution inversion of finite Fourier transform data through a localised polynomial approximation

摘要: The authors address the problem of high-resolution inversion finite Fourier transform data, which is frequently encountered in tomographic image reconstruction. A new parametric modelling approach, uses an adaptive localised polynomial approximation model object function, proposed to overcome Gibbs artifact and limited-resolution associated with conventional FFT methods. An algorithm for finding parameters given makes use linear prediction theory, singular-value decomposition least-squares fitting Reconstruction results from simulated real magnetic resonance experimental data are also presented demonstrate its capability ringing reduction resolution enhancement.