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Factorization model with total variation regularizer for image reconstruction and subgradient algorithm
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DOI：10.1016/j.patcog.2025.112038.png)
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Abstract
En 中文
• Factorized model with TV and ℓ2,0 surrogate for image reconstruction. • Subgradient algorithm for minimizing a locally weakly convex function. • Proved cluster points are stationary points, objective value sequence convergence. • Numerical experiments validate the efficiency of our method.
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7.6
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1.3W
Citations:
4.5W
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PATTERN RECOGNITION
PATTERN RECOGNITIONIF7.6
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