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arXiv · 1502.04981

Semi-supervised Segmentation Fusion of Multi-spectral and Aerial Images

Mete Ozay
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Abstract

A Semi-supervised Segmentation Fusion algorithm is proposed using consensus and distributed learning. The aim of Unsupervised Segmentation Fusion (USF) is to achieve a consensus among different segmentation outputs obtained from different segmentation algorithms by computing an approximate solution to the NP problem with less computational complexity. Semi-supervision is incorporated in USF using a new algorithm called Semi-supervised Segmentation Fusion (SSSF). In SSSF, side information about the co-occurrence of pixels in the same or different segments is formulated as the constraints of a convex optimization problem. The results of the experiments employed on artificial and real-world benchmark multi-spectral and aerial images show that the proposed algorithms perform better than the individual state-of-the art segmentation algorithms.

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Mete Ozay. 2015-02-26. Semi-supervised Segmentation Fusion of Multi-spectral and Aerial Images. https://doi.org/10.1109/icpr.2014.659

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