Image Segmentation Using a Trimmed Likelihood Estimator in the Asymmetric Mixture Model Based on Generalized Gamma and Gaussian Distributions

<div>Noisy synthetic data clustering using the considered methods. (a) Classical GMM, (b) FAST-TLE method, (c) CLO-TLE method, and (d) GGMM-TLE method.</div>

Mathematical Problems in Engineering

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Figure 1: Image Segmentation Using a Trimmed Likelihood Estimator in the Asymmetric Mixture Model Based on Generalized Gamma and Gaussian Distributions 

Figure 1 | Image Segmentation Using a Trimmed Likelihood Estimator in the Asymmetric Mixture Model Based on Generalized Gamma and Gaussian Distributions 