4 citations · 4 across the 6 of their papers we have counts for
6 papers
Non-convex regularization based on shrinkage penalty function
Manu Ghulyani, Muthuvel Arigovindan
Total Variation regularization (TV) is a seminal approach for image recovery. TV involves the norm of the image's gradient, aggregated over all pixel locations. Therefore, TV leads…
Compact Representation of n-th order TGV
Manu Ghulyani, Muthuvel Arigovindan
Although regularization methods based on derivatives are favored for their robustness and computational simplicity, research exploring higher-order derivatives remains limited. Thi…
Structurally Adaptive Multi-Derivative Regularization for Image Recovery from Sparse Fourier Samples
Sanjay Viswanath, Manu Ghulyani, Muthuvel Arigovindan
The importance of regularization has been well established in image reconstruction -- which is the computational inversion of imaging forward model -- with applications including d…
Generalized Hessian-Schatten Norm Regularization for Image Reconstruction
Manu Ghulyani, Deepak G Skariah, Muthuvel Arigovindan
Regularization plays a crucial role in reliably utilizing imaging systems for scientific and medical investigations. It helps to stabilize the process of computationally undoing an…
Fast roughness minimizing image restoration under mixed Poisson-Gaussian noise
Manu Ghulyani, Muthuvel Arigovindan
Image acquisition in many biomedical imaging modalities is corrupted by Poisson noise followed by additive Gaussian noise. While total variation and related regularization methods…
Image Restoration by Combined Order Regularization with Optimal Spatial Adaptation
Sanjay Viswanath, Simon de Beco, Maxime Dahan +1
Total Variation (TV) and related extensions have been popular in image restoration due to their robust performance and wide applicability. While the original formulation is still r…