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ORCIDGiuseppe Scarpa
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- affiliation: University of Naples Federico II, Italy
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2020 – today
- 2024
[j28]Matteo Ciotola
, Giuseppe Guarino, Giuseppe Scarpa:
An Unsupervised CNN-Based Pansharpening Framework with Spectral-Spatial Fidelity Balance. Remote. Sens. 16(16): 3014 (2024)- [j27]Giuseppe Guarino, Matteo Ciotola, Gemine Vivone, Giuseppe Scarpa:
Band-Wise Hyperspectral Image Pansharpening Using CNN Model Propagation. IEEE Trans. Geosci. Remote. Sens. 62: 1-18 (2024) - [c54]Giuseppe Guarino, Matteo Ciotola, Giovanni Poggi, Gemine Vivone, Giuseppe Scarpa:
Hybrid GSA-CNN Method for Hyperspectral Pansharpening. IGARSS 2024: 901-904 - [c53]Matteo Ciotola, Giuseppe Guarino, Giovanni Poggi, Giuseppe Scarpa:
Balancing Spectral and Spatial Quality in CNN-Based Unsupervised Pansharpening. IGARSS 2024: 1091-1094 - [c52]Matteo Ciotola, Giuseppe Guarino, Gemine Vivone, Jocelyn Chanussot, Antonio Plaza, Giuseppe Scarpa:
Hyperspectral Pansharpening: Review and Future Perspectives. IGARSS 2024: 1231-1234 - [c51]Giuseppe Guarino, Antonio Mazza, Giuliano Di Giuseppe, Giovanni Poggi, Gemine Vivone, Giuseppe Scarpa:
CNN-Based NO2 Estimation from Sentinel-5P Data: A Proof-of-Concept. IGARSS 2024: 5744-5747 - [i9]Matteo Ciotola, Giuseppe Guarino, Gemine Vivone, Giovanni Poggi, Jocelyn Chanussot, Antonio Plaza, Giuseppe Scarpa:
Hyperspectral Pansharpening: Critical Review, Tools and Future Perspectives. CoRR abs/2407.01355 (2024) - 2023
- [j26]Giuseppe Guarino, Matteo Ciotola, Gemine Vivone, Giovanni Poggi, Giuseppe Scarpa:
PCA-CNN Hybrid Approach for Hyperspectral Pansharpening. IEEE Geosci. Remote. Sens. Lett. 20: 1-5 (2023) - [j25]Matteo Ciotola, Giuseppe Scarpa:
Fast Full-Resolution Target-Adaptive CNN-Based Pansharpening Framework. Remote. Sens. 15(2): 319 (2023) - [j24]Matteo Ciotola, Giovanni Poggi, Giuseppe Scarpa:
Unsupervised Deep Learning-Based Pansharpening With Jointly Enhanced Spectral and Spatial Fidelity. IEEE Trans. Geosci. Remote. Sens. 61: 1-17 (2023) - [c50]Antonio Mazza, Matteo Ciotola, Giovanni Poggi, Giuseppe Scarpa:
Synergic Use of SAR and Optical Data for Feature Extraction. IGARSS 2023: 2061-2064 - [c49]Matteo Ciotola, Giuseppe Guarino, Antonio Mazza, Giovanni Poggi, Giuseppe Scarpa:
Pansharpening by Efficient and Fast Unsupervised Target-Adaptive CNN. IGARSS 2023: 5579-5582 - [c48]Giuseppe Guarino, Matteo Ciotola, Gemine Vivone, Giovanni Poggi, Giuseppe Scarpa:
An Unsupervised CNN-Based Hyperspectral Pansharpening Method. IGARSS 2023: 5982-5985 - [i8]Matteo Ciotola, Giovanni Poggi, Giuseppe Scarpa:
Unsupervised Deep Learning-based Pansharpening with Jointly-Enhanced Spectral and Spatial Fidelity. CoRR abs/2307.14403 (2023) - [i7]Matteo Ciotola, Mario Ragosta, Giovanni Poggi, Giuseppe Scarpa:
A full-resolution training framework for Sentinel-2 image fusion. CoRR abs/2307.14864 (2023) - [i6]Giuseppe Guarino, Matteo Ciotola, Gemine Vivone, Giuseppe Scarpa:
Band-wise Hyperspectral Image Pansharpening using CNN Model Propagation. CoRR abs/2311.06510 (2023) - 2022
- [j23]Francescopaolo Sica, Francesco Calvanese, Giuseppe Scarpa, Paola Rizzoli:
A CNN-Based Coherence-Driven Approach for InSAR Phase Unwrapping. IEEE Geosci. Remote. Sens. Lett. 19: 1-5 (2022) - [j22]Giuseppe Scarpa, Matteo Ciotola:
Full-Resolution Quality Assessment for Pansharpening. Remote. Sens. 14(8): 1808 (2022) - [j21]Matteo Ciotola, Sergio Vitale, Antonio Mazza, Giovanni Poggi, Giuseppe Scarpa:
Pansharpening by Convolutional Neural Networks in the Full Resolution Framework. IEEE Trans. Geosci. Remote. Sens. 60: 1-17 (2022) - [c47]Matteo Ciotola, Antonio Martinelli, Antonio Mazza, Giuseppe Scarpa:
An Adversarial Training Framework for Sentinel-2 Image Super-Resolution. IGARSS 2022: 3782-3785 - 2021
- [c46]Antonio Mazza, Giuseppe Scarpa, Luisa Verdoliva, Giovanni Poggi:
Impact of Training Set Design in CNN-Based Sar Image Despeckling. IGARSS 2021: 415-418 - [c45]Matteo Ciotola, Mario Ragosta, Giovanni Poggi, Giuseppe Scarpa:
A Full-Resolution Training Framework for Sentinel-2 Image Fusion. IGARSS 2021: 1260-1263 - [c44]Antonio Mazza, Pasquale Sepe, Giovanni Poggi, Giuseppe Scarpa:
Cloud Segmentation of Sentinel-2 Images Using Convolutional Neural Network with Domain Adaptation. IGARSS 2021: 7236-7239 - [i5]Giuseppe Scarpa, Matteo Ciotola:
Full-resolution quality assessment for pansharpening. CoRR abs/2108.06144 (2021) - [i4]Matteo Ciotola, Sergio Vitale, Antonio Mazza, Giovanni Poggi, Giuseppe Scarpa:
Pansharpening by convolutional neural networks in the full resolution framework. CoRR abs/2111.08334 (2021) - 2020
- [j20]Roberto Interdonato, Raffaele Gaetano, Danny Lo Seen, Mathieu Roche, Giuseppe Scarpa:
Extracting multilayer networks from Sentinel-2 satellite image time series. Netw. Sci. 8(S1): S26-S42 (2020) - [j19]Sergio Vitale, Giuseppe Scarpa:
A Detail-Preserving Cross-Scale Learning Strategy for CNN-Based Pansharpening. Remote. Sens. 12(3): 348 (2020) - [j18]Davide Cozzolino, Luisa Verdoliva, Giuseppe Scarpa, Giovanni Poggi:
Nonlocal CNN SAR Image Despeckling. Remote. Sens. 12(6): 1006 (2020) - [c43]Sergio Vitale, Giuseppe Scarpa:
A Cross-Scale Loss for CNN-Based Pansharpening. IGARSS 2020: 645-648 - [i3]Giulia Fracastoro, Enrico Magli, Giovanni Poggi, Giuseppe Scarpa, Diego Valsesia, Luisa Verdoliva:
Deep learning methods for SAR image despeckling: trends and perspectives. CoRR abs/2012.05508 (2020)
2010 – 2019
- 2019
- [j17]Massimiliano Gargiulo, Antonio Mazza, Raffaele Gaetano, Giuseppe Ruello, Giuseppe Scarpa:
Fast Super-Resolution of 20 m Sentinel-2 Bands Using Convolutional Neural Networks. Remote. Sens. 11(22): 2635 (2019) - [j16]Antonio Mazza, Francescopaolo Sica, Paola Rizzoli, Giuseppe Scarpa:
TanDEM-X Forest Mapping Using Convolutional Neural Networks. Remote. Sens. 11(24): 2980 (2019) - [j15]Sergio Vitale, Davide Cozzolino, Giuseppe Scarpa, Luisa Verdoliva, Giovanni Poggi:
Guided Patchwise Nonlocal SAR Despeckling. IEEE Trans. Geosci. Remote. Sens. 57(9): 6484-6498 (2019) - [c42]Davide Cozzolino, Luisa Verdoliva, Giuseppe Scarpa, Giovanni Poggi:
Nonlocal Sar Image Despeckling by Convolutional Neural Networks. IGARSS 2019: 5117-5120 - 2018
- [j14]Giuseppe Scarpa, Massimiliano Gargiulo, Antonio Mazza, Raffaele Gaetano:
A CNN-Based Fusion Method for Feature Extraction from Sentinel Data. Remote. Sens. 10(2): 236 (2018) - [j13]Giuseppe Scarpa, Sergio Vitale, Davide Cozzolino:
Target-Adaptive CNN-Based Pansharpening. IEEE Trans. Geosci. Remote. Sens. 56(9): 5443-5457 (2018) - [c41]Andrea De Giorgi, Gabriele Moser, Giovanni Poggi, Giuseppe Scarpa, Sebastiano B. Serpico:
Very High Resolution Optical Image Classification Using Watershed Segmentation and a Region-Based Kernel. IGARSS 2018: 1312-1315 - [c40]Antonio Marra, Massimiliano Gargiulo, Giuseppe Scarpa, Raffaele Gaetano:
Estimating the NDVI from SAR by Convolutional Neural Networks. IGARSS 2018: 1954-1957 - [c39]Massimiliano Gargiulo, Antonio Mazza, Raffaele Gaetano, Giuseppe Ruello, Giuseppe Scarpa:
A CNN-Based Fusion Method for Super-Resolution of Sentinel-2 Data. IGARSS 2018: 4713-4716 - [c38]Sergio Vitale, Giampaolo Ferraioli, Giuseppe Scarpa:
A CNN-Based Model for Pansharpening of WorldView-3 Images. IGARSS 2018: 5108-5111 - [i2]Sergio Vitale, Davide Cozzolino, Giuseppe Scarpa, Luisa Verdoliva, Giovanni Poggi:
Guided patch-wise nonlocal SAR despeckling. CoRR abs/1811.11872 (2018) - 2017
- [j12]Giovanni Chierchia, Mireille El Gheche, Giuseppe Scarpa, Luisa Verdoliva:
Multitemporal SAR Image Despeckling Based on Block-Matching and Collaborative Filtering. IEEE Trans. Geosci. Remote. Sens. 55(10): 5467-5480 (2017) - [c37]Giuseppe Masi, Davide Cozzolino, Luisa Verdoliva, Giuseppe Scarpa:
CNN-based pansharpening of multi-resolution remote-sensing images. JURSE 2017: 1-4 - [i1]Giuseppe Scarpa, Sergio Vitale, Davide Cozzolino:
Target-adaptive CNN-based pansharpening. CoRR abs/1709.06054 (2017) - 2016
- [j11]Giuseppe Masi, Davide Cozzolino, Luisa Verdoliva, Giuseppe Scarpa:
Pansharpening by Convolutional Neural Networks. Remote. Sens. 8(7): 594 (2016) - [j10]Diego Gragnaniello, Giovanni Poggi, Giuseppe Scarpa, Luisa Verdoliva:
SAR Image Despeckling by Soft Classification. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 9(6): 2118-2130 (2016) - 2015
- [j9]Stanislav Mikes, Michal Haindl, Giuseppe Scarpa, Raffaele Gaetano:
Benchmarking of Remote Sensing Segmentation Methods. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 8(5): 2240-2248 (2015) - [j8]Raffaele Gaetano, Giuseppe Masi, Giovanni Poggi, Luisa Verdoliva, Giuseppe Scarpa:
Marker-Controlled Watershed-Based Segmentation of Multiresolution Remote Sensing Images. IEEE Trans. Geosci. Remote. Sens. 53(6): 2987-3004 (2015) - [c36]Giuseppe Masi, Raffaele Gaetano, Giovanni Poggi, Giuseppe Scarpa:
Superpixel-based segmentation of remote sensing images through correlation clustering. IGARSS 2015: 1028-1031 - [c35]Diego Gragnaniello, Giovanni Poggi, Giuseppe Scarpa, Luisa Verdoliva:
SAR despeckling based on soft classification. IGARSS 2015: 2378-2381 - [c34]Giuseppe Masi, Raffaele Gaetano, Giovanni Poggi, Giuseppe Scarpa:
A ground truth design tool for multiresolution images. IGARSS 2015: 4999-5002 - 2014
- [j7]Davide Cozzolino, Sara Parrilli, Giuseppe Scarpa, Giovanni Poggi, Luisa Verdoliva:
Fast Adaptive Nonlocal SAR Despeckling. IEEE Geosci. Remote. Sens. Lett. 11(2): 524-528 (2014) - [j6]Raffaele Gaetano, Donato Amitrano, Giuseppe Masi, Giovanni Poggi, Giuseppe Ruello, Luisa Verdoliva, Giuseppe Scarpa:
Exploration of Multitemporal COSMO-SkyMed Data via Interactive Tree-Structured MRF Segmentation. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 7(7): 2763-2775 (2014) - [c33]Raffaele Gaetano, Donato Amitrano, Giuseppe Masi, Giovanni Poggi, Giuseppe Ruello, Luisa Verdoliva, Giuseppe Scarpa:
Interactive segmentation of high resolution synthetic aperture radar data by tree-structured MRF. IGARSS 2014: 3734-3737 - 2013
- [c32]Giuseppe Masi, Giuseppe Scarpa, Raffaele Gaetano, Giovanni Poggi:
A Watershed-Based Segmentation Technique for Multiresolution Data. ICIAP (1) 2013: 241-250 - [c31]Giuseppe Scarpa, Giuseppe Masi, Raffaele Gaetano, Luisa Verdoliva, Giovanni Poggi:
Dynamic Hierarchical Segmentation of Remote Sensing Images. ICIAP (1) 2013: 371-380 - 2012
- [c30]Raffaele Gaetano, Giuseppe Masi, Giuseppe Scarpa, Giovanni Poggi:
A marker-controlled watershed segmentation: Edge, mark and fill. IGARSS 2012: 4315-4318 - [c29]Giuseppe Scarpa, Giuseppe Masi, Luisa Verdoliva, Giovanni Poggi, Raffaele Gaetano:
Recursive-TFR Algorithm for Segmentation of Remotely Sensed Images. SITIS 2012: 174-181 - 2011
- [c28]Raffaele Gaetano, Josiane Zerubia, Giuseppe Scarpa, Giovanni Poggi:
Morphological road segmentation in urban areas from high resolution satellite images. DSP 2011: 1-8 - 2010
- [j5]Giuseppe Scarpa, Anna-Lena Idzko, Anandi Yadav, Stefan Thalhammer:
Organic ISFET Based on Poly (3-hexylthiophene). Sensors 10(3): 2262-2273 (2010) - [c27]Raffaele Gaetano, Giuseppe Scarpa, Tamás Szirányi:
Graph-based Analysis of Textured Images for Hierarchical Segmentation. BMVC 2010: 1-11 - [c26]Sara Parrilli, Mariana Poderico, Cesario Vincenzo Angelino, Giuseppe Scarpa, Luisa Verdoliva:
A nonlocal approach for SAR image denoising. IGARSS 2010: 726-729 - [c25]Giuseppe Masi, Raffaele Gaetano, Giuseppe Scarpa, Giovanni Poggi:
Dynamic segmentation for image information mining. IGARSS 2010: 1992-1995
2000 – 2009
- 2009
- [j4]Raffaele Gaetano, Giuseppe Scarpa, Giovanni Poggi:
Hierarchical Texture-Based Segmentation of Multiresolution Remote-Sensing Images. IEEE Trans. Geosci. Remote. Sens. 47(7-2): 2129-2141 (2009) - [j3]Giuseppe Scarpa, Raffaele Gaetano, Michal Haindl, Josiane Zerubia:
Hierarchical Multiple Markov Chain Model for Unsupervised Texture Segmentation. IEEE Trans. Image Process. 18(8): 1830-1843 (2009) - [c24]Raffaele Gaetano, Giuseppe Scarpa, Giovanni Poggi:
Recursive Texture Fragmentation and Reconstruction Segmentation Algorithm Applied to VHR Images. IGARSS (4) 2009: 101-104 - [c23]Raffaele Gaetano, Giuseppe Scarpa, Giovanni Poggi:
Advances in Texture-based Segmentation of High Resolution Remote Sensing Imagery. IGARSS (4) 2009: 105-108 - [c22]Raffaele Gaetano, Giuseppe Scarpa, Giovanni Poggi:
Texture-Based Segmentation of Very High Resolution Remote-Sensing Images. ISDA 2009: 578-583 - 2008
- [c21]Pietro Regoliosi, Andrea Vacchi, Giuseppe Scarpa, Paolo Lugli:
Quantum Cascade Lasers for Biosensing Applications. BIODEVICES (2) 2008: 87-93 - [c20]Raffaele Gaetano, Giuseppe Scarpa, Giovanni Poggi, Josiane Zerubia:
Unsupervised hierarchical image segmentation based on the TS-MRF model and fast Mean-Shift clustering. EUSIPCO 2008: 1-5 - [c19]Giuseppe Scarpa, Raffaele Gaetano, Giovanni Poggi:
Texture image segmentation by hierarchical modeling. EUSIPCO 2008: 1-5 - [c18]Raffaele Gaetano, Gabriele Moser, Giovanni Poggi, Giuseppe Scarpa, Sebastiano B. Serpico:
Region-Based Classification of Multisensor Optical-SAR Images. IGARSS (4) 2008: 81-84 - 2007
- [c17]Giuseppe Scarpa, Michal Haindl, Josiane Zerubia:
A Hierarchical Finite-State Model for Texture Segmentation. ICASSP (1) 2007: 1209-1212 - [c16]Raffaele Gaetano, Giuseppe Scarpa, Giovanni Poggi:
A hierarchical segmentation algorithm for multiresolution satellite images. IGARSS 2007: 1885-1888 - [c15]Michal Haindl, Stanislav Mikes, Giuseppe Scarpa:
Unsupervised Detection of Mammogram Regions of Interest. KES (3) 2007: 33-40 - [c14]Giuseppe Scarpa, Michal Haindl, Josiane Zerubia:
A Hierarchical Texture Model for Unsupervised Segmentation of Remotely Sensed Images. SCIA 2007: 303-312 - 2006
- [c13]Raffaele Gaetano, Giovanni Poggi, Giuseppe Scarpa:
Identification of image structure by the mean shift procedure for hierarchical MRF-based image segmentation. EUSIPCO 2006: 1-4 - [c12]Raffaele Gaetano, Giovanni Poggi, Giuseppe Scarpa:
Hierarchical Mrf-Based Segmentation of Remote-Sensing Images. ICIP 2006: 1121-1124 - [c11]Giuseppe Scarpa, Michal Haindl:
Unsupervised Texture Segmentation by Spectral-Spatial-Independent Clustering. ICPR (2) 2006: 151-154 - 2005
- [j2]Giovanni Poggi, Giuseppe Scarpa, Josiane Zerubia:
Supervised segmentation of remote sensing images based on a tree-structured MRF model. IEEE Trans. Geosci. Remote. Sens. 43(8): 1901-1911 (2005) - [c10]Marco Cagnazzo, Luca Cicala, Giovanni Poggi, Giuseppe Scarpa, Luisa Verdoliva:
An unsupervised segmentation-based coder for multispectral images. EUSIPCO 2005: 1-4 - [c9]Raffaele Gaetano, Giovanni Poggi, Giuseppe Scarpa:
Multitemporal image classification with automatic building of tree-structured MRF models. EUSIPCO 2005: 1-4 - 2004
- [b1]Giuseppe Scarpa:
Tree-structured Markov Random Field models for segmentation of noisy images with application to remote-sensing. University of Naples Federico II, Italy, 2004 - [c8]Giovanni Poggi, Giuseppe Scarpa, Josiane Zerubia:
Segmentation of remote-sensing images by supervised TS-MRF. ICIP 2004: 1867-1870 - [c7]Ciro D'Elia, Claudio Marrocco, Mario Molinara, Giovanni Poggi, Giuseppe Scarpa, Francesco Tortorella:
Detection of Microcalcifications Clusters in Mammograms through TS-MRF Segmentation and SVM-based Classification. ICPR (3) 2004: 742-745 - [c6]Marco Cagnazzo, Giovanni Poggi, Giuseppe Scarpa, Luisa Verdoliva:
Compression of multitemporal remote sensing images through Bayesian segmentation. IGARSS 2004: 83 - [c5]Luca Cicala, Giovanni Poggi, Giuseppe Scarpa:
Supervised segmentation of remote-sensing multitemporal images based on the tree-structured Markov random field model. IGARSS 2004: 1569-1572 - 2003
- [j1]Ciro D'Elia, Giovanni Poggi, Giuseppe Scarpa:
A tree-structured Markov random field model for Bayesian image segmentation. IEEE Trans. Image Process. 12(10): 1259-1273 (2003) - [c4]Ciro D'Elia, Giuseppe Scarpa:
Contour-Based Shape Representation for Image Compression and Analysis. DGCI 2003: 204-213 - [c3]Ciro D'Elia, Giovanni Poggi, Giuseppe Scarpa:
Sequential Bayesian segmentation of remote sensing images. ICIP (3) 2003: 985-988 - [c2]Ciro D'Elia, Giovanni Poggi, Giuseppe Scarpa:
Improved tree-structured segmentation of remote sensing images. IGARSS 2003: 1805-1807 - 2002
- [c1]Ciro D'Elia, Giovanni Poggi, Giuseppe Scarpa:
An adaptive MRF model for boundary-preserving segmentation of multispectral images. EUSIPCO 2002: 1-4
Coauthor Index
[c54] [c53] [c51] [i9] [j26] [j24] [c50] [c49] [c48] [i8] [i7] [j21] [c46] [c45] [c44] [i4] [j18] [i3] [j15] [c42] [c41] [i2] [j10] [j8] [c36] [c35] [c34] [j7] [j6] [c33] [c32] [c31] [c30] [c29] [c28] [c25] [j4] [c24] [c23] [c22] [c20] [c19] [c18] [c16] [c13] [c12] [j2] [c10] [c9] [c8] [c7] [c6] [c5] [j1] [c3] [c2] [c1]
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