activity
20172024
most citedPansharpening of PRISMA products for archaeological prospection

3 citations · 7 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2024★ 3 cited

Pansharpening of PRISMA products for archaeological prospection

Gregory Sech, Giulio Poggi, Marina Ljubenovic +2

Hyperspectral data recorded from satellite platforms are often ill-suited for geo-archaeological prospection due to low spatial resolution. The established potential of hyperspectr…

physics.optics2023★ 2 cited

Super-resolution of THz time-domain images based on low-rank representation

Marina Ljubenovic, Alessia Artesani, Stefano Bonetti +1

Terahertz time-domain spectroscopy (THz-TDS) employs sub-picosecond pulses to probe dielectric properties of materials giving as a result a 3-dimensional hyperspectral data cube. T…

cs.CV2023

Blind deblurring of hyperspectral document images

M. Ljubenovic, P. Guzzonato, G. Franceschin +1

Most computer vision and machine learning-based approaches for historical document analysis are tailored to grayscale or RGB images and thus, mostly exploit their spatial informati…

eess.IV2022★ 2 cited

Beam-Shape Effects and Noise Removal from THz Time-Domain Images in Reflection Geometry in the 0.25-6 THz Range

Marina Ljubenovic, Alessia Artesani, Stefano Bonetti +1

The increasing need of restoring high-resolution Hyper-Spectral (HS) images is determining a growing reliance on Computer Vision-based processing to enhance the clarity of the imag…

cs.CV2017

Blind image deblurring using class-adapted image priors

Marina Ljubenović, Mário A. T. Figueiredo

Blind image deblurring (BID) is an ill-posed inverse problem, usually addressed by imposing prior knowledge on the (unknown) image and on the blurring filter. Most of the work on B…