This paper studies the new Dirichlet Gaussian mixture model for image segmentation. First, we propose a new way to incorporate the local spatial information ...
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Oct 22, 2024 · This paper studies the new Dirichlet Gaussian mixture model for image segmentation. First, we propose a new way to incorporate the local spatial ...
The robustness, accuracy, and effectiveness of the proposed model in image segmentation are demonstrated through experiments on both natural images and ...
Mar 5, 2022 · This paper proposes and evaluates a method for segmentation of Hyperspectral Images using the Dirichlet Process Gaussian Mixture Model.
Dirichlet Gaussian mixture model: Application to image segmentation. https ... Image segmentation by Dirichlet process mixture model with generalised mean.
In our first experiment, we aimed to assess whether the Dirichlet process Gaussian mixture model could successfully segment grey matter (GM), white matter (WM) ...
The Gaussian-Hermite moment is applied to extract features to improve the robust of segmentation and reduce the influence of speckle noise. The effectiveness of ...
Oct 22, 2024 · Image segmentation is a key step for image processing and Gaussian Mixture Models(GMMs) are the common models for segmentation. The EM algorithm ...
Mixture models are popular statistical approaches for image segmentation. However, mixture models based segmentation faces some difficulties.
This paper proposes and evaluates a method for segmentation of Hyperspectral Images using the Dirichlet Process Gaussian Mixture Model, ...