Abstract Data fusion has always been a hot research topic in human-centric computing and extended with the development of artificial intelligence. Generally, the coupled data fusion algorithm usually utilizes the information from one data set to improve the estimation accuracy and explain related latent variables of other coupled datasets. This paper proposes several kinds of coupled images decomposition algorithms based on the coupled matrix and tensor factorization-optimization (CMTF-OPT) algorithm and the flexible coupling algorithm, which are termed the coupled images factorization-optimization (CIF-OPT) algorithm and the modified flexible coupling algorithm respectively. The theory and experiments show that the effect of the CIF-OPT algorithm is robust under the influence of different noises. Particularly, the CIF-OPT algorithm can accurately restore an image with missing some data elements. Moreover, the flexible coupling model has better estimation performance than a hard coupling. For high-dimensional images, this paper adopts the compressed data decomposition algorithm that not only works better than uncoupled ALS algorithm as the image noise level increases, but saves time and cost compared to the uncompressed algorithm.

Liangfu Lu

Xiaoxu Ren

Kuo-Hui Yeh

Zhiyuan Tan

Jocelyn Chanussot

Human-centric Computing and Information Sciences

在以人为中心的计算和信息科学（HCIS）中，KIPS-CSWRG 发表了高质量的论文，涵盖了与以人为中心的计算和信息科学相关的各种理论和实际应用。已发表的论文展示了对解决应用服务的各种问题以及 HCIS 范围内的其他问题具有重要价值的结果。此外，我们预计它们将引发与我们未来生活相关的进一步相关研究和技术改进。

The journal "Human-centric Computing and Information Sciences" focuses on Human-centric Computing and Information Sciences (HCIS) and is published by KIPS-CSWRG. It publishes high-quality papers covering various theoretical and practical applications related to HCIS. The published papers demonstrate significant contributions to solving various issues in applied services and other important problems within the HCIS domain. Furthermore, we anticipate that these studies will inspire further research and technological advancements related to our future lives.

《Human-centric Computing and Information Sciences》期刊专注于以人为中心的计算和信息科学（HCIS），由KIPS-CSWRG出版。期刊发表高质量的论文，涵盖与以人为中心的计算和信息科学相关的各种理论和实际应用。已发表的论文展示了对解决应用服务的各种问题以及HCIS领域内其他重要问题的显著贡献。此外，我们期待这些研究能够引发与未来生活相关的进一步研究和技术改进。

Category	Quartile
计算机科学	2
计算机科学, 计算机信息系统	2

Exploring coupled images fusion based on joint tensor decomposition

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Journal Info

Category	Quartile
COMPUTER SCIENCE, INFORMATION SYSTEMS	2