PUSHING THE LIMITS OF THE WIENER FILTER IN IMAGE DENOISING

被引：0
|
作者：
Bled, Clement [1 ]
Pitie, Francois [1 ]
机构：
[1] Trinity Coll Dublin, Dept Elect & Elect Engn, Dublin, Ireland
来源：
2023 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP | 2023年
基金：
爱尔兰科学基金会;
关键词：
Image Denoising; Wiener Filter;
D O I：
10.1109/ICIP49359.2023.10222826
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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 theWiener 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.
引用
收藏
页码：2590 / 2594
页数：5
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