@inproceedings{fba5233704da415aa2c4e0eccb422af6,
title = "Pan-Sharpening with a CNN-Based Two Stage Ratio Enhancement Method",
abstract = "We propose a hybrid method combining the deep learning technique and the ratio enhancement (RE) method for pansharpening. The intuition behind is to utilize the deep learning technique to synthesize a panchromatic (PAN) image for the RE method to reduce the spectral distortion while keeping the spatial details. The method consists of two stages. First, the CNN synthesizer is optimized to generate the downsampled PAN image to guarantee the network have a good initialization. Second, CNN is integrated into the RE method and supervised by the ground truth multi-spectral (MS) to produce an ideal synthesized PAN for the RE method. We conduct experiments on various datasets and compare with widely used methods to demonstrate the superiority of the proposed method.",
keywords = "Convolutional Neural Network (CNN), Image fusion, deep learning, pan-sharpening",
author = "Huanyu Zhou and Qingjie Liu and Qizhi Xu and Yunhong Wang",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 ; Conference date: 26-09-2020 Through 02-10-2020",
year = "2020",
month = sep,
day = "26",
doi = "10.1109/IGARSS39084.2020.9323505",
language = "英语",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "216--219",
booktitle = "2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Proceedings",
address = "美国",
}