arXiv:2303.16640
공식 코드 · Papers with Code
Pushing The Limits of the Wiener Filter in Image Denoising
원문 초록
As modern image denoiser networks have grown in size, their reported performance in popular real noise benchmarks such as DND and SIDD have now long outperformed classic non-deep learning denoisers such as Wiener and Wavelet-based methods. In this paper, we propose to revisit the Wiener filter and re-assess its potential performance. We show that carefully considering the implementation of the Wiener filter can yield similar performance to popular networks such as DnCNN.
함께 살펴볼 논문
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Optimal Density Functions for Weighted Convolution in Learning Models
Optimal Weighted Convolution for Classification and Denosing
Rotation-Equivariant Self-Supervised Method in Image Denoising
Degradation-Aware Feature Perturbation for All-in-One Image Restoration
토론
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