Spectral semi-blind deconvolution with hybrid regularization

A spectral semi-blind deconvolution with hybrid regularization (SBD-HR) is proposed to recover the spectrum and to estimate the parameter of the point spread function (PSF) adaptively. Firstly, a weighted Tikhonov regularization term about the spectrum is presented to preserve the details of spectrum. Then the regularization term about the PSF is modeled as L1-norm instead of L2-norm to enhance the stability of kernel estimation. The numerical solution processes for recovering the spectrum and for estimating the parameter of the PSF are deduced. Simulation results of infrared spectrum deconvolution demonstrate that the proposed method can recover the spectrum better from the degraded spectrum and estimate the parameter of the PSF accurately.