1 code implementation • 11 Nov 2023 • Giuseppe Guarino, Matteo Ciotola, Gemine Vivone, Giuseppe Scarpa
Hyperspectral pansharpening is receiving a growing interest since the last few years as testified by a large number of research papers and challenges.
no code implementations • 12 Oct 2023 • Kangqing Shen, Gemine Vivone, Xiaoyuan Yang, Simone Lolli, Michael Schmitt
To our knowledge, this is the first attempt to propose a research line for SAR colorization that includes a protocol, a benchmark, and a complete performance evaluation.
no code implementations • 14 Jul 2023 • ShangQi Deng, RuoCheng Wu, Liang-Jian Deng, Ran Ran, Gemine Vivone
In this paper, inspired by previous work of MHIF task, we realize that HR-MSI could serve as a high-frequency detail auxiliary input, leading us to propose a novel INR-based hyperspectral fusion function named Implicit Neural Feature Fusion Function (INF).
no code implementations • 4 Dec 2021 • Tian-Jing Zhang, Liang-Jian Deng, Ting-Zhu Huang, Jocelyn Chanussot, Gemine Vivone
Pansharpening refers to the fusion of a panchromatic image with a high spatial resolution and a multispectral image with a low spatial resolution, aiming to obtain a high spatial resolution multispectral image.
no code implementations • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2021 • Gemine Vivone, Mauro Dalla Mura, Andrea Garzelli, Fabio Pacifici
Comparative evaluation is a requirement for reproducible science and objective assessment of new algorithms.
no code implementations • 29 May 2020 • Jin-Fan Hu, Ting-Zhu Huang, Liang-Jian Deng, Tai-Xiang Jiang, Gemine Vivone, Jocelyn Chanussot
In order to alleviate this issue, in this work, we propose a simple and efficient architecture for deep convolutional neural networks to fuse a low-resolution hyperspectral image (LR-HSI) and a high-resolution multispectral image (HR-MSI), yielding a high-resolution hyperspectral image (HR-HSI).
no code implementations • 17 Apr 2015 • Laetitia Loncan, Luis B. Almeida, José M. Bioucas-Dias, Xavier Briottet, Jocelyn Chanussot, Nicolas Dobigeon, Sophie Fabre, Wenzhi Liao, Giorgio A. Licciardi, Miguel Simões, Jean-Yves Tourneret, Miguel A. Veganzones, Gemine Vivone, Qi Wei, Naoto Yokoya
In this work, we compare new pansharpening techniques designed for hyperspectral data with some of the state of the art methods for multispectral pansharpening, which have been adapted for hyperspectral data.