{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T16:27:35Z","timestamp":1770913655593,"version":"3.50.1"},"reference-count":77,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2020,7,19]],"date-time":"2020-07-19T00:00:00Z","timestamp":1595116800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61976174, 61877049, 11671317 and 11991023"],"award-info":[{"award-number":["61976174, 61877049, 11671317 and 11991023"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2018AAA0102201"],"award-info":[{"award-number":["2018AAA0102201"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In the literature of pan-sharpening based on neural networks, high resolution multispectral images as ground-truth labels generally are unavailable. To tackle the issue, a common method is to degrade original images into a lower resolution space for supervised training under the Wald\u2019s protocol. In this paper, we propose an unsupervised pan-sharpening framework, referred to as \u201cperceptual pan-sharpening\u201d. This novel method is based on auto-encoder and perceptual loss, and it does not need the degradation step for training. For performance boosting, we also suggest a novel training paradigm, called \u201cfirst supervised pre-training and then unsupervised fine-tuning\u201d, to train the unsupervised framework. Experiments on the QuickBird dataset show that the framework with different generator architectures could get comparable results with the traditional supervised counterpart, and the novel training paradigm performs better than random initialization. When generalizing to the IKONOS dataset, the unsupervised framework could still get competitive results over the supervised ones.<\/jats:p>","DOI":"10.3390\/rs12142318","type":"journal-article","created":{"date-parts":[[2020,7,20]],"date-time":"2020-07-20T10:59:38Z","timestamp":1595242778000},"page":"2318","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":50,"title":["PercepPan: Towards Unsupervised Pan-Sharpening Based on Perceptual Loss"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1510-3881","authenticated-orcid":false,"given":"Changsheng","family":"Zhou","sequence":"first","affiliation":[{"name":"The School of Mathematics and Statistics, Xi\u2019an Jiaotong University, No.28 Xianning West Road, Xi\u2019an 710049, China"}]},{"given":"Jiangshe","family":"Zhang","sequence":"additional","affiliation":[{"name":"The School of Mathematics and Statistics, Xi\u2019an Jiaotong University, No.28 Xianning West Road, Xi\u2019an 710049, China"}]},{"given":"Junmin","family":"Liu","sequence":"additional","affiliation":[{"name":"The School of Mathematics and Statistics, Xi\u2019an Jiaotong University, No.28 Xianning West Road, Xi\u2019an 710049, China"}]},{"given":"Chunxia","family":"Zhang","sequence":"additional","affiliation":[{"name":"The School of Mathematics and Statistics, Xi\u2019an Jiaotong University, No.28 Xianning West Road, Xi\u2019an 710049, China"}]},{"given":"Rongrong","family":"Fei","sequence":"additional","affiliation":[{"name":"The School of Mathematics and Statistics, Xi\u2019an Jiaotong University, No.28 Xianning West Road, Xi\u2019an 710049, China"}]},{"given":"Shuang","family":"Xu","sequence":"additional","affiliation":[{"name":"The School of Mathematics and Statistics, Xi\u2019an Jiaotong University, No.28 Xianning West Road, Xi\u2019an 710049, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,7,19]]},"reference":[{"key":"ref_1","first-page":"459","article-title":"The use of intensity-hue-saturation transformations for merging SPOT panchromatic and multispectral image data","volume":"56","author":"Carper","year":"1990","journal-title":"Photogramm. 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