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A novel benchmark dataset of color steel sheds for remote sensing image retrieval

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Abstract

Benchmark datasets play an important role in evaluating remote sensing image retrieval (RSIR) methods. The current datasets cover many scene categories, but omit an important scene of color steel sheds, which are widely distributed with a large number on the earth’s surface. Therefore, we propose a new benchmark dataset of color steel sheds (CSS) from Google map imagery for RSIR and share it open access in our V-RSIR system. The new dataset has rich intra-class and inter-class diversity, and is composed of blue, red and white color steel sheds with the total number of 2407 remote sensing images. We conduct evaluation experiments on the new dataset by using ten low/mid feature-based and ten deep learning feature-based methods. Experimental results indicate that the dataset is effective for evaluating RSIR methods and using the dataset can construct an effective retrieval model for color steel sheds. Besides, we have experimentally demonstrated that color constancy does affect retrieval performance on our CSS dataset. Furthermore, some experiments of merging the CSS dataset with the PatternNet, VGoogle and NWPU45 datasets are also conducted. Experimental results demonstrate that our dataset can be used as a complement to other retrieval datasets. Furthermore, these experimental results can be used as baseline for future applications on RSIR.

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Acknowledgements

The authors would like to thank the PatternNet, NWPU45 and other datasets for their open access. The authors also would like to thank the editors and the anonymous reviewers for their constructive comments and suggestions.

Funding

This work was supported in part by Yunnan Fundamental Research Projects under Grant 202001AS070032, and in part by the National Natural Science Foundation of China under Grant 41801308, and in part by the National Key Research and Development Program of China under Grant 2018YFB0505002.

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Authors and Affiliations

  1. School of Geosciences and Info-Physics, Central South University, Changsha, 410083, People’s Republic of China

    Dongyang Hou & Siyuan Wang

  2. School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan, 250101, People’s Republic of China

    Huaqiao Xing

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  1. Dongyang Hou
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Correspondence to Huaqiao Xing.

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Hou, D., Wang, S. & Xing, H. A novel benchmark dataset of color steel sheds for remote sensing image retrieval. Earth Sci Inform 14, 809–818 (2021). https://doi.org/10.1007/s12145-021-00593-7

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