← Search

Abijith Jagannath Kamath

9 accepted papers

2025

Neuromorphic Unlimited Sampling for High-Dynamic-Range Video Acquisition

ICASSP 2025accepted

The unlimited sampling framework (USF) is a computational sensing paradigm that addresses the practical bottleneck pertaining to finite dynamic range and quantization resolution of standard analog-to-digital converters (ADCs). The essence of unlimited sampling is to capture high-dynamic range (HDR)…

Cited by 0SourceScholar
2025

On the Design of Weakly-Convex Regularizers for Solving Linear Inverse Problems

ICASSP 2025accepted

Linear inverse problems are ubiquitous in signal processing and computational imaging. The prototypical problem is to recover a signal from noisy linear measurements. A typical optimization-based approach is to minimize the sum of a data-fidelity loss and a regularization function. The data-fidelity…

Cited by 0SourceScholar
2024

Image Restoration with Generalized L2 Loss and Convergent Plug-and-Play Priors

ICASSP 2024accepted

Image restoration involves solving an optimization problem where the objective function is the sum of a data-fidelity term and a regularization functional that incorporates a desired image prior. Solving the optimization problem using proximal methods results in iterative algorithms that require com…

Cited by 0SourceScholar
2024

Variational Analysis of Adversarial Regularization for Solving Inverse Problems

ICASSP 2024accepted

Inverse problems form the backbone of modern signal/image processing and computational imaging, where signal reconstruction from corrupted measurements follows an optimization problem. The objective function is the sum of a data-fidelity term and a regularization functional that enforces desired pro…

Cited by 0SourceScholar
2023

Multichannel Time-Encoding of Finite-Rate-of-Innovation Signals

ICASSP 2023accepted

Time-encoding of continuous-time signals is an alternative sampling paradigm to Shannon sampling. In time-encoding or event-driven sampling, the signal is encoded using a sequence of time instants corresponding to an event. In this paper, we propose multichannel time-encoding of signals with a finit…

Cited by 0SourceScholar
2022

Differentiate-and-Fire Time-Encoding of Finite-Rate-of-Innovation Signals

ICASSP 2022accepted

Time-encoding or event-driven sampling of continuous-time signals is an alternative paradigm to uniform sampling. In this sampling scheme, the signal is encoded by a sequence of time-instants as opposed to a sequence of amplitudes in uniform sampling. Time-encoding is opportunistic by design – measu…

Cited by 0SourceScholar
2020

A Time-Based Sampling Framework for Finite-Rate-of-Innovation Signals

ICASSP 2020accepted

Time-based sampling of continuous-time signals is an alternative to Shannon's sampling paradigm in which the signal is encoded using a sequence of nonuniform time instants. The standard methods for reconstructing signals in bandlimited and shift-invariant spaces from their nonuniform measurements em…

Cited by 0SourceScholar