Introduction - If you have any usage issues, please Google them yourself
The enclosed code provides the implementation of the above three deconvolution strategies. To start, users should check the file demo.m. The deconvolution subroutine is implemented in the following files: deconvL2 frequency. M: deconvolution in frequency domain, assuming that the Gauss derivative is ahead. 2. DeconvL2. M: uses the conjugate gradient algorithm to assume the existence of Gauss derivative prior deconvolution in the spatial domain. 3.deconvSps. M: Using iterative weighted least squares algorithm, a sparse derivative prior deconvolution is assumed in the spatial domain. Users should note that all of the above functions assume that the convolution filter has an odd number of pixels on both dimensions.