Abstract
Image analysis usually refers to processing of images with the objective of finding objects presented in the image. The extraction and the analysis of image data is a fundamental step for image segmentation, in this work a new method allowing the evolution of the threshold satellite image defined and based on the optimization multi-objective for segmentation of Worldview images and funded on the Tsallis and the Rényi entropies. The Objective is the reclassification of all unclassified pixels by the previous method in 2017. The improved analysis and the optimized method multi-objective thresholding are proposed. First, respectively for each Worldview image selected, the optimal thresholds for all the criteria used in this study is find. Finally, by using the evaluation criteria corresponding to the Levine and Nazif criteria and the criteria of the mean square error, in order to challenge the performance of this method to that previously developed in 2017. The results obtained by this approach were very satisfactory and the efficacy of this method confirmed. This method overcomes the difficulties of the method previously developed in 2017 and obtained results that are more precise. Therefore, the new method based on multi-objective optimization contribute significantly to performance.
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A COMSTECH TWAS 2015 Research Grant Award supported the satellite image used for this work partially.
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Mechkouri, S.E., El Joumani, S., Zennouhi, R. et al. Multi-objective optimization for worldview image segmentation funded on the entropies of Tsallis and Rényi. Multimed Tools Appl 79, 30637–30652 (2020). https://doi.org/10.1007/s11042-020-09572-4
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DOI: https://doi.org/10.1007/s11042-020-09572-4