{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T14:16:16Z","timestamp":1753884976320,"version":"3.41.2"},"reference-count":40,"publisher":"World Scientific Pub Co Pte Ltd","issue":"01","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Image Grap."],"published-print":{"date-parts":[[2022,1]]},"abstract":"<jats:p> Inspite of technological advancement, inherent processing capability of current age sensors limits the desired details in the acquired image for variety of remote sensing applications. Pan-sharpening is a prominent scheme to integrate the essential spatial details inferred from panchromatic (PAN) image and the desired spectral information of multispectral (MS) image. This paper presents an effective two-stage pan-sharpening method to produce high resolution multispectral (HRMS) image. The proposed method is based on the premise that the HRMS image can be formulated as an amalgam of spectral and spatial components. The spectral components are estimated by processing the interpolated MS image with a filter approximated with modulation transfer function (MTF) of the sensor. Sparse representation theory is adapted to construct the spatial components. The high-frequency details extracted from the PAN image and its low resolution variant are utilized to construct dual dictionaries. The dictionaries are jointly learned by an efficient training algorithm to enhance the adaptability. The hypothesis of sparse coefficients invariance over scales is also incorporated to reckon the appropriate spatial information. Further, an iterative filtering mechanism is developed to enhance the quality of fused image. Four distinct datasets generated from QuickBird, IKONOS, Pl\u00e9iades and WorldView-2 sensors are used for experimentation. The comprehensive assessment at reduced-scale and full-scale persuade the effectiveness of proposed method in the retention of spectral information and intensification of the spatial details. <\/jats:p>","DOI":"10.1142\/s0219467822500073","type":"journal-article","created":{"date-parts":[[2021,4,23]],"date-time":"2021-04-23T07:36:46Z","timestamp":1619163406000},"source":"Crossref","is-referenced-by-count":6,"title":["A Two-Stage PAN-Sharpening Algorithm Based on Sparse Representation for Spectral Distortion Reduction"],"prefix":"10.1142","volume":"22","author":[{"given":"Rajesh","family":"Gogineni","sequence":"first","affiliation":[{"name":"Department of Electronics and Communications Engineering, Chalapathi Institute of Technology, A. R. Nagar, Guntur 522016, Andhra Pradesh, India"}]},{"given":"Dhara J.","family":"Sangani","sequence":"additional","affiliation":[{"name":"ECE Department, Vishwakarma Government Engineering College, Chandkheda 382424, Gujarat, India"}]}],"member":"219","published-online":{"date-parts":[[2021,4,22]]},"reference":[{"key":"S0219467822500073BIB001","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2014.2361734"},{"key":"S0219467822500073BIB002","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2016.03.003"},{"key":"S0219467822500073BIB003","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2020.11.001"},{"key":"S0219467822500073BIB004","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2004.834804"},{"key":"S0219467822500073BIB005","first-page":"295","volume":"57","author":"Chavez P.","year":"1991","journal-title":"Photogramm. Eng. Rem. 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