Compensating for nonstationary blurring by further blurring and deconvolution

In many imaging systems, the point spread function (PSF) is non-stationary. Usually a computation-intensive iterative algorithm is used to de-blur the non-stationary PSF. This paper presents a new idea of using a non-iterative method to compensate for the spatially variant PSF. This method first further blurs the image with a non-stationary kernel so that the resultant image has a stationary PSF, then deblurs the resultant image using an efficient decovolution technique. The proposed method is illustrated and implemented by SPECT (single photon emission computed tomography) applications.