Search Results for author:
Found 8 papers, 0 papers with code
Robust Alignment for Panoramic Stitching via an Exact Rank Constraint
We study the problem of image alignment for panoramic stitching.
Deep Algorithm Unrolling for Blind Image Deblurring
We then unroll the algorithm to construct a neural network for image deblurring which we refer to as Deep Unrolling for Blind Deblurring (DUBLID).
An Algorithm Unrolling Approach to Deep Image Deblurring
We first present an iterative algorithm that may be considered a generalization of the traditional total-variation regularization method on the gradient domain, and subsequently unroll the half-quadratic splitting algorithm to construct a neural network.
Prior Information Guided Regularized Deep Learning for Cell Nucleus Detection
Using a set of canonical cell nuclei shapes, prepared with the help of a domain expert, we develop a new approach that we call Shape Priors with Convolutional Neural Networks (SP-CNN).
Blind Image Deblurring Using Row-Column Sparse Representations
Blind image deblurring is a particularly challenging inverse problem where the blur kernel is unknown and must be estimated en route to recover the deblurred image.
Phase and TV Based Convex Sets for Blind Deconvolution of Microscopic Images
Therefore, the set of images with a prescribed FT phase can be used as a constraint set in blind deconvolution problems.
Denosing Using Wavelets and Projections onto the L1-Ball
In sparsity based denoising methods, it is assumed that the original signal is sparse in some transform domains such as the wavelet domain and the wavelet subsignals of the noisy signal are projected onto L1-balls to reduce noise.
Signal Reconstruction Framework Based On Projections Onto Epigraph Set Of A Convex Cost Function (PESC)
A new signal processing framework based on making orthogonal Projections onto the Epigraph Set of a Convex cost function (PESC) is developed.
