K3DN: Disparity-Aware Kernel Estimation for Dual-Pixel Defocus Deblurring

Yan Yang, Liyuan Pan*, Liu Liu, Miao Miao Liu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Citations (Scopus)

Abstract

The dual-pixel (DP) sensor captures a two-view image pair in a single snapshot by splitting each pixel in half. The disparity occurs in defocus blurred regions between the two views of the DP pair, while the in-focus sharp regions have zero disparity. This motivates us to propose a K3DN framework for DP pair deblurring, and it has three modules: i) a disparity-aware deblur module. It estimates a disparity feature map, which is used to query a trainable kernel set to estimate a blur kernel that best describes the spatially-varying blur. The kernel is constrained to be symmetrical per the DP formulation. A simple Fourier transform is performed for deblurring that follows the blur model; ii) a reblurring regularization module. It reuses the blur kernel, performs a simple convolution for reblurring, and regularizes the estimated kernel and disparity feature unsupervisedly, in the training stage; iii) a sharp region preservation module. It identifies in-focus regions that correspond to areas with zero disparity between DP images, aims to avoid the introduction of noises during the deblurring process, and improves image restoration performance. Experiments on four standard DP datasets show that the proposed K3DN outperforms state-of-the-art methods, with fewer parameters and flops at the same time.

Original languageEnglish
Title of host publicationProceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023
PublisherIEEE Computer Society
Pages13263-13272
Number of pages10
ISBN (Electronic)9798350301298
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023 - Vancouver, Canada
Duration: 18 Jun 202322 Jun 2023

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume2023-June
ISSN (Print)1063-6919

Conference

Conference2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023
Country/TerritoryCanada
CityVancouver
Period18/06/2322/06/23

Keywords

  • Computational imaging

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Yang, Y., Pan, L., Liu, L., & Liu, M. M. (2023). K3DN: Disparity-Aware Kernel Estimation for Dual-Pixel Defocus Deblurring. In Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023 (pp. 13263-13272). (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; Vol. 2023-June). IEEE Computer Society. https://doi.org/10.1109/CVPR52729.2023.01274