Deep, convergent, unrolled half-quadratic splitting for image
deconvolution
Deep, convergent, unrolled half-quadratic splitting for image
deconvolution
In recent years, algorithm unrolling has emerged as a powerful technique for designing interpretable neural networks based on iterative algorithms. Imaging inverse problems have particularly benefited from unrolling-based deep network design since many traditional model-based approaches rely on iterative optimization. Despite exciting progress, typical unrolling approaches heuristically design layer-specific convolution …