An improved image deconvolution approach using local constraint

Conventional deblurring approaches such as the Richardson–Lucy (RL) algorithm will introduce strong noise and ringing artifacts, though the point spread function (PSF) is known. Since it is difficult to estimate an accurate PSF in real imaging system, the results of those algorithms will be worse. A spatial weight matrix (SWM) is adopted as local constraint, which is incorporated into image statistical prior to improve the RL approach. Experiments show that our approach can make a good balance between preserving image details and suppressing ringing artifacts and noise.

► We improve RL algorithm for deblurring both natural and remote sensing images. ► Image derivative prior is adopted. ► Spatial weight matrix is introduced as local constraint. ► We try a smoothing step into iteration process for further suppressing ringing. ► Our method makes a good balance between preserving details and suppressing ringing.