Consistency Center-Based Deep Cross-Modal Hashing for Multisource Remote Sensing Image Retrieval
Yuxi Sun, Yunming Ye, Jian She Kang, Rubén Fernández-Beltrán, Xutao Li, Zhenyu Xiong, Xu Huang, Antonio Plaza · IEEE Transactions on Geoscience and Remote Sensing · 2023
Cross-modal hashing aims to retrieve similar images from large-scale Earth Observation (EO) data archives, which typically contain multiple satellite sources of remote sensing (RS) images. However, existing cross-modal hashing methods primarily focus on dual-source RS images and often face two main limitations when retrieving multi-source RS images. Firstly, these methods exhibit significant redundancy as they require handling all possible dual-source combinations in multi-source RS images. Secondly, they often rely on pairwise or triplet image sources to construct objective functions, which are not significantly effective in reducing the discrepancies among multiple RS image sources. To address these limitations, we propose a novel Consistency Center-based deep cross-modal Hashing method called C2Hash for multi-source RS image retrieval. Our C2Hash employs a multi-branch hashing network to directly encode multi-source RS images into unified hash codes, thereby offering higher processing efficiency. Furthermore, C2Hash introduces consistency centers to construct a novel objective function. The consistency center represents the shared semantic features among similar multi-source RS images and is generated by a label hashing network. The objective function encourages similar multi-source RS images to approach the same consistency center to align all image sources in a unified Hamming space. Our method can effectively reduce the discrepancies across multiple image sources and generate unified hash codes. To evaluate its effectiveness, we construct a new Multi-Source RS Image dataset called MSRSI, comprising five different types of image sources. We conduct comprehensive experiments to demonstrate the superior performance of our method on the MSRSI dataset. https://github.com/sunyuxi/C2Hash.