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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)…

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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…

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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…

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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…

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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…

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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…

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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…

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