1 citations · 2 across the 11 of their papers we have counts for
12 papers
Diffusion Meets Unrolling: Compressive SAR Image Reconstruction with Interleaved Learned Corrections
Odysseas Pappas, Andrew C. M. Austin, Perla Mayo +2
Compressive Synthetic Aperture Radar (SAR) imaging, typically formulated as an inverse problem and solved with traditional iterative optimisation methods, can be very computational…
NASTaR: NovaSAR Automated Ship Target Recognition Dataset
Benyamin Hosseiny, Kamirul Kamirul, Odysseas Pappas +1
Synthetic Aperture Radar (SAR) offers a unique capability for all-weather, space-based maritime activity monitoring by capturing and imaging strong reflections from ships at sea. A…
Physics-Informed Diffusion Models for SAR Ship Wake Generation from Text Prompts
Kamirul Kamirul, Odysseas Pappas, Alin Achim
Detecting ship presence via wake signatures in SAR imagery is attracting considerable research interest, but limited annotated data availability poses significant challenges for su…
R-Sparse R-CNN: SAR Ship Detection Based on Background-Aware Sparse Learnable Proposals
Kamirul Kamirul, Odysseas Pappas, Alin Achim
We introduce R-Sparse R-CNN, a novel pipeline for oriented ship detection in Synthetic Aperture Radar (SAR) images that leverages sparse learnable proposals enriched with backgroun…
Diffusion Probabilistic Models for Compressive SAR Imaging
Odysseas Pappas, Perla Mayo, Andrew Austin +1
Compressed sensing Synthetic Aperture Radar (SAR) image formation, formulated as an inverse problem and solved with traditional iterative optimization methods can be very computati…
Deep Unfolded Approximate Message Passing for Quantitative Acoustic Microscopy Image Reconstruction
Odysseas Pappas, Jonathan Mamou, Adrian Basarab +2
Quantitative Acoustic Microscopy (QAM) is an imaging technology utilising high frequency ultrasound to produce quantitative two-dimensional (2D) maps of acoustical and mechanical p…
Sparse R-CNN OBB: Ship Target Detection in SAR Images Based on Oriented Sparse Proposals
Kamirul Kamirul, Odysseas Pappas, Alin Achim
We present Sparse R-CNN OBB, a novel framework for the detection of oriented objects in SAR images leveraging sparse learnable proposals. The Sparse R-CNN OBB has streamlined archi…
On the Modelling of Ship Wakes in S-Band SAR Images and an Application to Ship Identification
Kamirul Kamirul, Odysseas Pappas, Igor G. Rizaev +1
We present a novel ship wake simulation system for generating S-band Synthetic Aperture Radar (SAR) images, and demonstrate the use of such imagery for the classification of ships…
High-resolution Coastline Extraction in SAR Images via MISP-GGD Superpixel Segmentation
Odysseas Pappas, Nantheera Anantrasirichai, Byron Adams +1
High accuracy coastline/shoreline extraction from SAR imagery is a crucial step in a number of maritime and coastal monitoring applications. We present a method based on image segm…
Sparse InSAR Data 3D Inpainting for Ground Deformation Detection Along the Rail Corridor
Odysseas Pappas, Juliet Biggs, David Bull +2
Monitoring of ground movement close to the rail corridor, such as that associated with landslips caused by ground subsidence and/or uplift, is of great interest for the detection a…
Sparse regularization with a non-convex penalty for SAR imaging and autofocusing
Zi-Yao Zhang, Odysseas Pappas, Igor G. Rizaev +1
In this paper, SAR image reconstruction with joint phase error estimation (autofocusing) is formulated as an inverse problem. An optimization model utilising a sparsity-enforcing C…
SAR Image Autofocusing using Wirtinger calculus and Cauchy regularization
Zi-Yao Zhang, Odysseas Pappas, Alin Achim
In this paper, an optimization model using Cauchy regularization is proposed for simultaneous SAR image reconstruction and autofocusing. A coordinate descent framework in which the…