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Convergent Plug-and-Play Image Restoration with Annealed Noise Levels
Plug-and-Play (PnP) methods solve imaging inverse problems by incorporating deep denoisers into iterative optimization algorithms. Although practical implementations often decrease the denoiser noise level $σ$ along iterations, most existing convergence analyses assume a fixed denoiser. In this work
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