16 citations · 20 across the 18 of their papers we have counts for
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DIPA: Distilled Preconditioned Algorithms for Solving Imaging Inverse Problems
Romario Gualdrón-Hurtado, Roman Jacome, Leon Suarez +1
Solving imaging inverse problems has usually been addressed by designing proper prior models of the underlying signal. However, minimizing the data fidelity term poses significant…
UTOPY: Unrolling Algorithm Learning via Fidelity Homotopy for Inverse Problems
Roman Jacome, Romario Gualdrón-Hurtado, Leon Suarez-Rodriguez +1
Imaging Inverse problems aim to reconstruct an underlying image from undersampled, coded, and noisy observations. Within the wide range of reconstruction frameworks, the unrolling…
Deep Distillation Gradient Preconditioning for Inverse Problems
Romario Gualdrón-Hurtado, Roman Jacome, Leon Suarez +2
Imaging inverse problems are commonly addressed by minimizing measurement consistency and signal prior terms. While huge attention has been paid to developing high-performance prio…
Distilling Knowledge for Designing Computational Imaging Systems
Leon Suarez-Rodriguez, Roman Jacome, Henry Arguello
Designing the physical encoder is crucial for accurate image reconstruction in computational imaging (CI) systems. Currently, these systems are designed via end-to-end (E2E) optimi…
Learning Point Spread Function Invertibility Assessment for Image Deconvolution
Romario Gualdrón-Hurtado, Roman Jacome, Sergio Urrea +2
Deep-learning (DL)-based image deconvolution (ID) has exhibited remarkable recovery performance, surpassing traditional linear methods. However, unlike traditional ID approaches th…
DUF: Deep Coded Aperture Design and Unrolling Algorithm for Compressive Spectral Image Fusion
Roman Jacome, Jorge Bacca, Henry Arguello
Compressive spectral imaging (CSI) has attracted significant attention since it employs synthetic apertures to codify spatial and spectral information, sensing only 2D projections…