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The problem of generating a corresponding super-resolution (SR) image from a single low-resolution (LR) image is addressed via the join operation in the paper. Firstly, the LR image is partitioned into some patches, each patch is represented as the sphere granule set. Secondly, the join operation between two adjacent image patches is used to compensate the pixel value of SR image. Experimental results showed the feasibility and superiority via join operation by root mean square errors (RMSE) between the reconstructed SR image and the original image compared with bicubic interpolation and NNLasso.<\/jats:p>","DOI":"10.1142\/s0218001417540209","type":"journal-article","created":{"date-parts":[[2017,3,10]],"date-time":"2017-03-10T04:26:49Z","timestamp":1489120009000},"page":"1754020","source":"Crossref","is-referenced-by-count":3,"title":["Super-Resolution Reconstruction from Single Image Based on Join Operation in Granular Computing"],"prefix":"10.1142","volume":"31","author":[{"given":"Hongbing","family":"Liu","sequence":"first","affiliation":[{"name":"Center of Computing, Xinyang Normal University, Xinyang 464000, P. R. China"}]},{"given":"Wenyong","family":"Zhou","sequence":"additional","affiliation":[{"name":"Center of Computing, Xinyang Normal University, Xinyang 464000, P. R. 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