Foveated Non-local Means Image Denoising Using Wiener filter Center Weight
- Resource Type
- Conference
- Authors
- Zhang, Xiaobo
- Source
- 2023 9th Annual International Conference on Network and Information Systems for Computers (ICNISC) ICNISC Network and Information Systems for Computers (ICNISC), 2023 9th Annual International Conference on. :340-343 Oct, 2023
- Subject
- Computing and Processing
Computers
Wiener filters
Visual systems
Information filters
Noise measurement
Information systems
Image denoising
non-local means (NLM)
foveated self-similarity (FSS)
windowed self-similarity (WSS)
Wiener filter center weight (WFCW)
- Language
Inspired by the human visual system (HVS), Alessandro Foi et al. design a foveation operator to calculate the similarity of patch. The calculation of similarity is called the foveated self-similarity (FSS). Their study shows that FSS is much superior to the traditional windowed self-similarity (WSS). Non-local means (NLM) with FSS (NLM-FSS) produces a more satisfactory denoising effect. However, as with many NLMs with WSS (NLM-WSS), center weight is not considered sufficiently. This study shows that window based Wiener filter center weight proposed by Zhang also can improve the NLM-FSS.