{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,3,30]],"date-time":"2023-03-30T07:19:49Z","timestamp":1680160789604},"reference-count":19,"publisher":"World Scientific Pub Co Pte Lt","issue":"02","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Image Grap."],"published-print":{"date-parts":[[2021,4]]},"abstract":"<jats:p> The satellite image classification plays a vital role in remote sensing for analyzing the images and recognizing the patterns. Supervised classification is one of the methods in which pixels of an image are grouped based on training samples. The uncertainty is one of the major issues in a supervised classification, where the pixel is classified into more than one class. This is happened due to the use of spectral values without considering contextual values in classification. Hence, this paper proposes Cellular Automata (CA)-based Classifier for Satellite Images Classification, where spectral values are combined with contextual values to improve the accuracy of the classifier. The proposed CA classifier combines the spectral values with contextual values in iteration until the uncertainty is resolved. Thereby, the proposed scheme improves the accuracy of the classical supervised classifier of parallel piped, minimum distance, DSVM and KNN classifier by 7% at an average. <\/jats:p>","DOI":"10.1142\/s0219467821500145","type":"journal-article","created":{"date-parts":[[2020,10,31]],"date-time":"2020-10-31T07:36:47Z","timestamp":1604129807000},"page":"2150014","source":"Crossref","is-referenced-by-count":1,"title":["Satellite Image Classification Using Cellular Automata"],"prefix":"10.1142","volume":"21","author":[{"given":"S.","family":"Poonkuntran","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Velammal College of Engineering and Technology, Viraganoor, Madurai, Tamil Nadu 625009, India"}]},{"given":"P.","family":"Alli","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Velammal College of Engineering and Technology, Viraganoor, Madurai, Tamil Nadu 625009, India"}]},{"given":"T. M. Senthil","family":"Ganesan","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Velammal College of Engineering and Technology, Viraganoor, Madurai, Tamil Nadu 625009, India"}]},{"given":"S. Manthira","family":"Moorthi","sequence":"additional","affiliation":[{"name":"Indian Space Research Organization \u2013 Space, Application Centre, Ahmedabad, India"}]},{"given":"M. P.","family":"Oza","sequence":"additional","affiliation":[{"name":"Indian Space Research Organization \u2013 Space, Application Centre, Ahmedabad, India"}]}],"member":"219","published-online":{"date-parts":[[2021,1,21]]},"reference":[{"key":"S0219467821500145BIB001","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511812903","volume-title":"Physical Principles of Remote Sensing","author":"Rees W. G.","year":"2001","edition":"2"},{"key":"S0219467821500145BIB002","first-page":"502","volume-title":"Proc. 7th Int. Conf. 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