Image Denoising Using the Split Bregman Algorithm
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Resource Overview
Implementation of image denoising via the Split Bregman algorithm with rapid convergence and edge-preserving characteristics
Detailed Documentation
Employing the Split Bregman algorithm for image denoising significantly accelerates convergence while preserving edge features, thereby effectively enhancing image quality. The method typically involves iteratively solving optimization problems through variable splitting and Bregman iteration, where key components include L1-regularized minimization for edge preservation and efficient numerical solvers for improved computational performance.
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