A Local Search-Based GeneSIS algorithm for the Segmentation and Classification of Remote-Sensing Images
@article{Mylonas2016ALS, title={A Local Search-Based GeneSIS algorithm for the Segmentation and Classification of Remote-Sensing Images}, author={Stelios K. Mylonas and Dimitris G. Stavrakoudis and Ioannis B. Theocharis and George C. Zalidis and Ioannis Z. Gitas}, journal={IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing}, year={2016}, volume={9}, pages={1470-1492} }
A local search-based version of the so-called genetic sequential image segmentation (GeneSIS) algorithm is presented in this paper, for the classification of remotely sensed images. The new method combines the properties of the GeneSIS framework with the principles of the region growing segmentation algorithms. Localized GeneSIS operates on a fine-segmented image obtained after preliminary watershed transformation. Segmentation proceeds by iterative expansions emanating from object cores, i.e… CONTINUE READING
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References
Publications referenced by this paper.
SHOWING 1-10 OF 43 REFERENCES
A Marker-Based Approach for the Automated Selection of a Single Segmentation From a Hierarchical Set of Image Segmentations
VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL
Best Merge Region-Growing Segmentation With Integrated Nonadjacent Region Object Aggregation
VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL