A Weighted Non-convex Restoration Model for Hyperspectral Image.

Low-rank and sparsity are two popular regularization objects in hyperspectral image restoration. To generalize this decomposition, a weighted non-convex low-rank method is proposed by adopting non-convex \(l_p\)-norm (\(0

Keywords:

• Artificial intelligence
• Hyperspectral imaging
• Computer science
• Image (mathematics)
• Regular polygon
• Computer vision

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