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It can be reduced by adding spatial detail images of the PAN image into MS images. In the convolution neural network\u2013 (CNN) based method, the lowpass filter image extracted by the CNN model when MS and PAN images are directly applied into the input. The feature values are very high and reduce the conversion efficiency. In the proposed scheme, bi-dimensional empirical mode decomposition is used to extract the spatial detail information of the PAN image to reduce the feature values of the input. This extracted PAN image information is applied to the CNN to produce the non-linear changes in the image pixels and transformed into the perfect spatial detail image. It identifies the spatial and spectral detail quantity for the proposed scheme and it also varies with the different datasets automatically of the same satellite images. Simulation results in the context of qualitative and quantitative analysis demonstrate the effectiveness of proposed scheme applied on datasets collected by different satellites.<\/jats:p>","DOI":"10.1145\/3506709","type":"journal-article","created":{"date-parts":[[2022,3,4]],"date-time":"2022-03-04T10:31:58Z","timestamp":1646389918000},"page":"1-22","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Pansharpening Scheme Using Bi-dimensional Empirical Mode Decomposition and Neural Network"],"prefix":"10.1145","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2598-2314","authenticated-orcid":false,"given":"Nidhi","family":"Saxena","sequence":"first","affiliation":[{"name":"Technology Information Forecasting and Assessment Council (TIFAC) Core, Vellore Institute of Technology, Vellore, TN, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Balasubramanian","family":"Raman","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Indian Institute of Technology, Roorkee, Uttarakhand, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,3,4]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/DFUA.2003.1219964"},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.14358\/PERS.72.5.591"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2013.09.007"},{"key":"e_1_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.14358\/PERS.74.2.193"},{"key":"e_1_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2007.904923"},{"key":"e_1_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2905511"},{"issue":"3","key":"e_1_3_1_8_2","first-page":"295","article-title":"Comparison of three different methods to merge multiresolution and multispectral data- landsat TM and SPOT panchromatic","volume":"57","author":"Chavez Pats","year":"1991","unstructured":"Pats Chavez, Stuart C. 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