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Classification of remotely sensed images using decimal coded morphological profiles

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Abstract

In this paper, we propose a novel method for pixel classification of remotely sensed images. The proposed method exploits the spatial information of image pixels using morphological profiles produced by structuring elements of different sizes and shapes. Morphological profiles produced by multiple structuring elements are combined into a single feature by decimal coding. The advantage of proposed feature is that it can effectively utilize the potential of multiple morphological profiles without increasing the complexity of feature space. The proposed approach was tested on remotely sensed images with known ground truths, and performance was improved up to 27 % in the overall accuracy results over existing techniques.

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Authors and Affiliations

  1. National University of Sciences and Technology, Islamabad, Pakistan

    Hasnat Khurshid & M. Faisal Khan

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  1. Hasnat Khurshid
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  2. M. Faisal Khan
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Correspondence to Hasnat Khurshid.

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Khurshid, H., Khan, M.F. Classification of remotely sensed images using decimal coded morphological profiles. SIViP 10, 1001–1007 (2016). https://doi.org/10.1007/s11760-015-0851-8

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  • DOI: https://doi.org/10.1007/s11760-015-0851-8

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