K. Slepova
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Combined Multi-stage PDE-Based Image Processing
Computational Aspects
Image processing techniques play an important role in tasks such as denoising, segmentation, and analysis of diverse image datasets. In this paper, we will investigate the computational aspects of a combined multi-stage PDE-based image processing approach. This approach consists of three stages: image formation, noise filtering, relying upon nonlinear diffusion, and image segmentation. These stages can be combined into one nonlinear optimisation problem which is then solved using the alternating direction method of multipliers (ADMM). We evaluate the performance of the method using a 3D MR image.
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Image processing techniques play an important role in tasks such as denoising, segmentation, and analysis of diverse image datasets. In this paper, we will investigate the computational aspects of a combined multi-stage PDE-based image processing approach. This approach consists of three stages: image formation, noise filtering, relying upon nonlinear diffusion, and image segmentation. These stages can be combined into one nonlinear optimisation problem which is then solved using the alternating direction method of multipliers (ADMM). We evaluate the performance of the method using a 3D MR image.