Abstract
We propose a block-based signal-dependent noise estimation method on videos, that leverages inter-frame redundancy to separate noise from signal. Block matching is applied to find block pairs between two consecutive frames with similar signal. Then the Ponomarenko et al. method is extended to video by sorting pairs by their low-frequency energy and estimating noise in the high frequencies. Experiments on a real dataset of drone videos show its performance for different parameter settings and different noise levels. Two extensions of the proposed method using subpixel matching and for multiscale noise estimation are respectively analyzed.
| Original language | English |
|---|---|
| Pages (from-to) | 280-313 |
| Number of pages | 34 |
| Journal | Image Processing On Line |
| Volume | 13 |
| Early online date | 9 Nov 2023 |
| DOIs | |
| Publication status | Published - 2023 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2023 IPOL & the authors.
Funding
This work was supported by grants from ANR (APATE, ANR-22-CE39-0016), Horizon Europe VERA.AI (No. 101070093), Rgion le-de-France and UDOPIA (ANR-20-THIA-0013). Centre Borelli is also a member of Universit Paris Cit, SSA and INSERM.
Keywords
- image processing
- noise estimation
- noise level function
- video processing
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