NDLI: Automatic panoramic stitching of omni-directional remote sensing images

Content Provider	IEEE Xplore Digital Library
Author	Xingxing Li Zhenming Yuan
Copyright Year	2013
Description	Author affiliation: Coll. of Inf. Sci. & Eng., Hangzhou Normal Univ., Hangzhou, China (Xingxing Li; Zhenming Yuan)
Abstract	Panoramic stitching of multiple high-resolution remote sensing images still faces the accuracy and the speed difficulties. This paper proposed an automatic panoramic stitching algorithm to register multiple omni-directional remote sensing images, which utilizes Location Sensitive Hashing (LSH) to accelerate the rough feature matching, and combines the Euclidean distance ratio and the median filter to achieve the stable homographic transform. The decision of the reference image from the multiple images is judged by the most sum of the overlapping matches density. Experimental results show that the proposed method can get faster registration speed than the iterative method under the comparable accuracy.
Sponsorship	IEEE Eng.Med. Biol. Soc.
Starting Page	352
Ending Page	357
File Size	588696
Page Count	6
File Format	PDF
e-ISBN	9781479927647
DOI	10.1109/CISP.2013.6744017
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	LSH Matched filters median filtering Panoramic stitching Euclidean distance Filtering algorithms Feature extraction Remote sensing image Vectors Digital filters Remote sensing Euclidean distance ratio
Content Type	Text
Resource Type	Article

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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