4 citations · 8 across the 12 of their papers we have counts for
12 papers
PSTAIC regularization for 2D spatiotemporal image reconstruction
Deepak G Skariah, Muthuvel Arigovindan
We propose a model for restoration of spatio-temporal TIRF images based on infimal decomposition regularization model named STAIC proposed earlier. We propose to strengthen the STA…
STAIC regularization for spatio-temporal image reconstruction
Deepak G Skariah, Muthuvel Arigovindan
We propose a regularization-based image restoration scheme for 2D images recorded over time (2D+t). We design an infimal convolution-based regularization function which we call spa…
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…
PAT image reconstruction using augmented sparsity regularization with practicable tuning of regularization weight
Nadaparambil Aravindakshan Rejesh, Muthuvel Arigovindan
Among all tissue imaging modalities, photo-acoustic tomography (PAT) has been getting increasing attention in the recent past due to the fact that it has high contrast, high penetr…
Photo-acoustic tomographic image reconstruction from reduced data using physically inspired regularization
Nadaparambil Aravindakshan Rejesh, Sandeep Kumar Kalva, Manojit Pramanik +1
We propose a model-based image reconstruction method for photoacoustic tomography(PAT) involving a novel form of regularization and demonstrate its ability to recover good quality…
Generalized Multi-Order Total Variation for Signal Restoration
Sanjay Viswanath, Muthuvel Arigovindan
Total Variation (TV) based regularization has been widely applied in restoration problems due to its simple derivative filters based formulation and robust performance. While first…
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…
Image Reconstruction from Undersampled Confocal Microscopy Data using Multiresolution Based Maximum Entropy Regularization
Bibin Francis, Manoj Mathew, Muthuvel Arigovindan
We consider the problem of reconstructing 2D images from randomly under-sampled confocal microscopy samples. The well known and widely celebrated total variation regularization, wh…