利用基于多模式和多阶梯度张量的 l1/2 稀疏模型，以贝叶斯方法融合多光谱和全色图像

IF 1.4 4区地球科学 Q3 IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY

Remote Sensing Letters Pub Date : 2024-04-26 DOI:10.1080/2150704x.2024.2337823

Pengfei Liu, Nan Huang, Zhizhong Zheng

引用次数: 0

摘要

在这封信中，我们基于张量表示建模，提出了一种基于梯度张量的多模多阶非凸模型（M2GTNM），用于多光谱（MS）和粒度（PS）的贝叶斯融合。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Bayesian fusion of multispectral and panchromatic images using a multi-mode and multiorder gradient tensor-based l1/2 sparse model

In this letter, based on the tensor representation modelling, we propose a multi-mode and multi-order gradient tensor-based non-convex model (M2GTNM) for Bayesian fusion of multispectral (MS) and p...

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来源期刊

Remote Sensing Letters REMOTE SENSING-IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY

CiteScore

4.10

自引率

4.30%

发文量

审稿时长

6-12 weeks

期刊介绍： Remote Sensing Letters is a peer-reviewed international journal committed to the rapid publication of articles advancing the science and technology of remote sensing as well as its applications. The journal originates from a successful section, of the same name, contained in the International Journal of Remote Sensing from 1983 –2009. Articles may address any aspect of remote sensing of relevance to the journal’s readership, including – but not limited to – developments in sensor technology, advances in image processing and Earth-orientated applications, whether terrestrial, oceanic or atmospheric. Articles should make a positive impact on the subject by either contributing new and original information or through provision of theoretical, methodological or commentary material that acts to strengthen the subject.