Abstract
In this study we present the model-based clustering in order to overcome the problem of mixed pixels for satellite imagery. The mixed pixel problem is one of the major reasons that affect the classification accuracy in the classification of remotely sensed images. Mixed pixels are usually the prime reason for degrading the success in image classification and object recognition. A modified model-based clustering algorithm is developed by modifying membership function and compared with the traditional model-based clustering algorithm in terms of classification error and brier score. Results on classification of satellite images reveal that the suggestive algorithms are robust and effective.
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The research of the last listed author was performed under the development program of Volga Region Mathematical Center (agreement no. 075-02-2023-944).
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Sherwani, A.R., Ali, Q.M., Ali, I. et al. A Modified Mixture Model-Based Clustering Algorithm for Resolving the Problem of Mixed Pixels Available in Satellite Imagery. Lobachevskii J Math 44, 4824–4838 (2023). https://doi.org/10.1134/S199508022311029X
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DOI: https://doi.org/10.1134/S199508022311029X