2017
Automatic parameter tuning for image denoising with learned sparsifying transforms
ICASSP 2017accepted
Data-driven and learning-based sparse signal models outperform analytical models (e.g, wavelets), for image denoising, but require careful parameter tuning to reach peak performance. In this work, we provide a solution to the problem of parameter tuning for image denoising with transform sparsity re…