ALGORITHM FOR MINIMIZING LATENT SHARP IMAGE COST FUNCTION AND POINT SPREAD FUNCTION COST FUNCTION WITH A SPATIAL MASK IN A REGULARIZATION TERM

摘要

A method for deblurring a blurry image (18) includes utilizing a spatial mask and a variable splitting technique in the latent sharp image estimation cost function. Additionally or alternatively, the method can include the utilizing a spatial mask and a variable splitting technique in the PSF estimation cost function. The spatial mask can be in a regularization term of either or both the latent sharp image estimation cost function and the PSF cost function. The latent sharp image estimation cost function can be used for non-blind deconvolution. Alternatively, one or both cost functions can be used for blind deconvolution.

主权项

1. A method for deblurring a blurry image, the method comprising the steps of:
utilizing a first spatial mask in a fidelity term and a second spatial mask in a regularization term of a latent sharp image estimation cost function used for deconvolution of the blurry image; and utilizing a variable splitting technique in the latent sharp image function, the variable splitting technique including introducing a first auxiliary variable and a first penalty term into the latent sharp image estimation cost function to split the operations of convolution and element-wise multiplication.