Kalman filtering of patches for frame-recursive video denoising

Pablo ARIAS, Jean-Michel MOREL

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

16 Citations (Scopus)

Abstract

A frame recursive video denoising method computes each output frame as a function of only the current noisy frame and the previous denoised output. Frame recursive methods were among the earliest approaches for video denoising. However in the last fifteen years they have been used almost exclusively for real-time applications with denoising performance far from being state-of-the-art. In this work we propose a simple frame recursive method which is fast, has a low memory complexity and achieves results competitive with more complex state-of-the-art methods that require processing several input frames for producing each output frame. Furthermore, in terms of visual quality, the proposed approach is able to recover many details that are missed by most non-recursive methods. As an additional contribution we also propose an off-line post-processing of the denoised video that boosts denoising quality and temporal consistency.
Original languageEnglish
Title of host publicationProceedings - 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019
Pages1917-1926
Number of pages10
ISBN (Electronic)9781728125060
DOIs
Publication statusPublished - 16 Jun 2019
Externally publishedYes

Publication series

NameIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Volume2019-June
ISSN (Print)2160-7508
ISSN (Electronic)2160-7516

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Funding

Acknowledgments. Work partly financed by IDEX Paris-Saclay IDI 2016, ANR-11-IDEX-0003-02, Office of Naval research grant N00014-17-1-2552, DGA Astrid project «filmer la Terre» no ANR-17-ASTR-0013-01, MENRT.

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