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

Figure 7

Segmentation performance comparison for real-world images in the Gaussian noise environment (zero mean, variance 0.01). From the first row to the last: noisy image, GMM, SMM, GMM, NSMM, ACAP, and GGMM-TLE, respectively. From the first column to the last column: test image 24063, 8068, 241004, 55067, and 35010 (Berkeley Dataset).