Name
Title | ||
|---|---|---|
A simple blind-denoising filter inspired by electrically coupled photoreceptors in the retina. |
Abstract | ||
|---|---|---|
Photoreceptors in the retina are coupled by electrical synapses called junctions. It has long been established that gap junctions increase the signal-to-noise ratio of photoreceptors. Inspired by electrically coupled photoreceptors, we introduced a simple filter, the PR-filter, with only one variable. On BSD68 dataset, PR-filter showed outstanding performance in SSIM during blind denoising tasks. It also significantly improved the performance of state-of-the-art convolutional neural network blind denosing on non-Gaussian noise. The performance of keeping more details might be attributed to small receptive field of the photoreceptors. |
Year | Venue | Field |
|---|---|---|
2018 | arXiv: Computer Vision and Pattern Recognition | Receptive field,Noise reduction,Gap junction,Pattern recognition,Convolutional neural network,Computer science,Retina,Artificial intelligence,Electrical Synapses |
DocType | Volume | Citations |
Journal | abs/1806.05882 | 1 |
PageRank | References | Authors |
0.37 | 5 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yang Yue | 1 | 74 | 13.76 |
| Liuyuan He | 2 | 1 | 0.37 |
| Gan He | 3 | 1 | 0.37 |
| Jian K. Liu | 4 | 20 | 8.77 |
| Kai Du | 5 | 18 | 2.52 |
| Yonghong Tian | 6 | 1057 | 102.81 |
| Tiejun Huang | 7 | 1281 | 120.48 |