{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T17:57:50Z","timestamp":1770832670004,"version":"3.50.1"},"reference-count":46,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2024,12,10]],"date-time":"2024-12-10T00:00:00Z","timestamp":1733788800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["42171326"],"award-info":[{"award-number":["42171326"]}]},{"name":"National Natural Science Foundation of China","award":["LR23D010001"],"award-info":[{"award-number":["LR23D010001"]}]},{"name":"National Natural Science Foundation of China","award":["LY22F010014"],"award-info":[{"award-number":["LY22F010014"]}]},{"name":"National Natural Science Foundation of China","award":["2022J076"],"award-info":[{"award-number":["2022J076"]}]},{"name":"National Natural Science Foundation of China","award":["2021Z107"],"award-info":[{"award-number":["2021Z107"]}]},{"name":"Zhejiang Provincial Natural Science Foundation of China","award":["42171326"],"award-info":[{"award-number":["42171326"]}]},{"name":"Zhejiang Provincial Natural Science Foundation of China","award":["LR23D010001"],"award-info":[{"award-number":["LR23D010001"]}]},{"name":"Zhejiang Provincial Natural Science Foundation of China","award":["LY22F010014"],"award-info":[{"award-number":["LY22F010014"]}]},{"name":"Zhejiang Provincial Natural Science Foundation of China","award":["2022J076"],"award-info":[{"award-number":["2022J076"]}]},{"name":"Zhejiang Provincial Natural Science Foundation of China","award":["2021Z107"],"award-info":[{"award-number":["2021Z107"]}]},{"name":"Ningbo Natural Science Foundation","award":["42171326"],"award-info":[{"award-number":["42171326"]}]},{"name":"Ningbo Natural Science Foundation","award":["LR23D010001"],"award-info":[{"award-number":["LR23D010001"]}]},{"name":"Ningbo Natural Science Foundation","award":["LY22F010014"],"award-info":[{"award-number":["LY22F010014"]}]},{"name":"Ningbo Natural Science Foundation","award":["2022J076"],"award-info":[{"award-number":["2022J076"]}]},{"name":"Ningbo Natural Science Foundation","award":["2021Z107"],"award-info":[{"award-number":["2021Z107"]}]},{"name":"2025 Science and Technology Major Project of Ningbo City","award":["42171326"],"award-info":[{"award-number":["42171326"]}]},{"name":"2025 Science and Technology Major Project of Ningbo City","award":["LR23D010001"],"award-info":[{"award-number":["LR23D010001"]}]},{"name":"2025 Science and Technology Major Project of Ningbo City","award":["LY22F010014"],"award-info":[{"award-number":["LY22F010014"]}]},{"name":"2025 Science and Technology Major Project of Ningbo City","award":["2022J076"],"award-info":[{"award-number":["2022J076"]}]},{"name":"2025 Science and Technology Major Project of Ningbo City","award":["2021Z107"],"award-info":[{"award-number":["2021Z107"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Pan-sharpening aims to generate high-resolution (HR) multispectral (MS) images by fusing HR panchromatic (PAN) and low-resolution (LR) MS images covering the same area. However, due to the lack of real HR MS reference images, how to accurately evaluate the quality of a fused image without reference is challenging. On the one hand, most methods evaluate the quality of the fused image using the full-reference indices based on the simulated experimental data on the popular Wald\u2019s protocol; however, this remains controversial to the full-resolution data fusion. On the other hand, existing limited no reference methods, most of which depend on manually crafted features, cannot fully capture the sensitive spatial\/spectral distortions of the fused image. Therefore, this paper proposes a perceptual quality assessment method based on deep feature similarity measure. The proposed network includes spatial\/spectral feature extraction and similarity measure (FESM) branch and overall evaluation network. The Siamese FESM branch extracts the spatial and spectral deep features and calculates the similarity of the corresponding pair of deep features to obtain the spatial and spectral feature parameters, and then, the overall evaluation network realizes the overall quality assessment. Moreover, we propose to quantify both the overall precision of all the training samples and the variations among different fusion methods in a batch, thereby enhancing the network\u2019s accuracy and robustness. The proposed method was trained and tested on a large subjective evaluation dataset comprising 13,620 fused images. The experimental results suggested the effectiveness and the competitive performance.<\/jats:p>","DOI":"10.3390\/rs16244621","type":"journal-article","created":{"date-parts":[[2024,12,10]],"date-time":"2024-12-10T04:15:03Z","timestamp":1733804103000},"page":"4621","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Perceptual Quality Assessment for Pansharpened Images Based on Deep Feature Similarity Measure"],"prefix":"10.3390","volume":"16","author":[{"given":"Zhenhua","family":"Zhang","sequence":"first","affiliation":[{"name":"Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shenfu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiangchao","family":"Meng","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liang","family":"Chen","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2495-9924","authenticated-orcid":false,"given":"Feng","family":"Shao","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,10]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"A Blind Full-Resolution Quality Evaluation Method for Pansharpening","volume":"60","author":"Meng","year":"2022","journal-title":"IEEE Trans. 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