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DC Field | Value | Language |
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dc.contributor.author | Suresh, S. | |
dc.contributor.author | Das, D. | |
dc.contributor.author | Lal, S. | |
dc.date.accessioned | 2020-03-30T09:59:12Z | - |
dc.date.available | 2020-03-30T09:59:12Z | - |
dc.date.issued | 2018 | |
dc.identifier.citation | 2017 9th International Conference on Advanced Computing, ICoAC 2017, 2018, Vol., , pp.9-14 | en_US |
dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/7478 | - |
dc.description.abstract | Researches in satellite image enhancement have been particularly confined to two major areas-contrast enhancement and image de noising of remote sensing images. The processing of relatively dark or shadowed images necessitates the need for robust remote sensing enhancement techniques. In this paper, a robust framework for quality enhancement of multispectral remote sensing images is proposed. The quantitative results of proposed algorithm and other existing remote sensing enhancement algorithms are calculated in terms of DE, NIQMC, BIQME, PisDist and CM on different remote sensing and other image databases. Results reveal that visual enhancement of the proposed algorithm is better than other existing remote sensing enhancement algorithms. Finally, the simulation experimental results show that proposed algorithm is effective and efficient for remotes sensing as well as natural images. � 2017 IEEE. | en_US |
dc.title | A Framework for Quality Enhancement of Multispectral Remote Sensing Images | en_US |
dc.type | Book chapter | en_US |
Appears in Collections: | 2. Conference Papers |
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