Bidirectional Motion Estimation with Cyclic Cost Volume for High Dynamic Range Imaging

We propose a high dynamic range (HDR) imaging algorithm based on bidirectional motion estimation. First, we develop a motion estimation network with the cyclic cost volume and spatial attention maps to estimate accurate optical flows between input low dynamic range (LDR) images. Then, we develop the...

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Bibliographic Details
Published in2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) pp. 1182 - 1189
Main Authors Vien, An Gia, Park, Seonghyun, Mai, Truong Thanh Nhat, Kim, Gahyeon, Lee, Chul
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2022
Subjects
Costs
Dynamic range
Heuristic algorithms
Imaging
Motion estimation
Optical filters
Tracking
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Summary:We propose a high dynamic range (HDR) imaging algorithm based on bidirectional motion estimation. First, we develop a motion estimation network with the cyclic cost volume and spatial attention maps to estimate accurate optical flows between input low dynamic range (LDR) images. Then, we develop the dynamic local fusion network that combines the warped and reference inputs to generate a synthesized image by exploiting local information. Finally, to further improve the synthesis performance, we develop the global refinement network that generates a residual image by exploiting global information. Experimental results on the dataset from the NTIRE 2022 HDR Challenge Track 1 (Low-complexity constrain) demonstrate the effectiveness of the proposed HDR image synthesis algorithm.
ISSN:2160-7516
DOI:10.1109/CVPRW56347.2022.00125