@inproceedings{378fc78e7e084473a4ef5fae0872f3e4,
title = "DEEP CONVOLUTIONAL SPARSE CODING NETWORK FOR PANSHARPENING WITH GUIDANCE OF SIDE INFORMATION",
abstract = "Pansharpening is a fundamental issue in remote sensing field. This paper proposes a side information partially guided convolutional sparse coding (SCSC) model for pansharpening. The key idea is to split the low resolution multispectral image into a panchromatic image related feature map and a panchromatic image irrelated feature map, where the former one is regularized by the side information from panchromatic images. With the principle of algorithm unrolling techniques, the proposed model is generalized as a deep neural network, called as SCSC pansharpening neural network (SCSC-PNN). Compared with 13 classic and state-of-the-art methods on three satellites, the numerical experiments show that SCSC-PNN is superior to others. The codes are available at https://github.com/xsxjtu/SCSC-PNN.",
keywords = "Pan-sharpening, algorithm unrolling, convolutional sparse coding, image fusion",
author = "Shuang Xu and Jiangshe Zhang and Kai Sun and Zixiang Zhao and Lu Huang and Junmin Liu and Chunxia Zhang",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE; 2021 IEEE International Conference on Multimedia and Expo, ICME 2021 ; Conference date: 05-07-2021 Through 09-07-2021",
year = "2021",
doi = "10.1109/ICME51207.2021.9428131",
language = "英语",
series = "Proceedings - IEEE International Conference on Multimedia and Expo",
publisher = "IEEE Computer Society",
booktitle = "2021 IEEE International Conference on Multimedia and Expo, ICME 2021",
}