Geometry-based PSF estimation and deblurring of defocused images with depth information

Yiqun Wu; Chao Sun; Bing Zeng; Dehua Xie; Shuaicheng Liu; Xianzhong Chen

doi:10.1109/VCIP.2016.7805485

Geometry-based PSF estimation and deblurring of defocused images with depth information

Yiqun Wu, Chao Sun, Bing Zeng, Dehua Xie, Shuaicheng Liu, Xianzhong Chen

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

2 Citations (Scopus)

Abstract

We propose in this paper an algorithm to recover the blurred details of an image caused by defocusing during the photo-taking. Our algorithm takes one RGB image as well as its depth map as the input. We build up a model in which each captured image pixel is regarded as a light-emitting source that goes through a synthetic camera system. Thanks to the depth map, we have the geometrical information of the scene so that the point spread function (PSF) can be derived for each pixel more accurately as compared to conventional approaches where only RGB images are involved. Then, we make use of the derived PSFs to solve an optimization so as to reconstruct an all-in-focus image. The reconstructed results are evaluated by comparison with the original all-in-focus images. Compared to other methods for the deblurring of defocused images, our method shows a better recovery of image details.

Original language	English
Title of host publication	VCIP 2016 - 30th Anniversary of Visual Communication and Image Processing
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509053162
DOIs	https://doi.org/10.1109/VCIP.2016.7805485
Publication status	Published - 4 Jan 2017
Externally published	Yes
Event	2016 IEEE Visual Communication and Image Processing, VCIP 2016 - Chengdu, China Duration: 27 Nov 2016 → 30 Nov 2016

Publication series

Name	VCIP 2016 - 30th Anniversary of Visual Communication and Image Processing

Conference

Conference	2016 IEEE Visual Communication and Image Processing, VCIP 2016
Country/Territory	China
City	Chengdu
Period	27/11/16 → 30/11/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

Defocus deblurring
Depth map
point spread function (PSF)
synthetic camera system

Access to Document

10.1109/VCIP.2016.7805485

Cite this

Wu, Y., Sun, C., Zeng, B., Xie, D., Liu, S., & Chen, X. (2017). Geometry-based PSF estimation and deblurring of defocused images with depth information. In VCIP 2016 - 30th Anniversary of Visual Communication and Image Processing Article 7805485 (VCIP 2016 - 30th Anniversary of Visual Communication and Image Processing). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VCIP.2016.7805485

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abstract = "We propose in this paper an algorithm to recover the blurred details of an image caused by defocusing during the photo-taking. Our algorithm takes one RGB image as well as its depth map as the input. We build up a model in which each captured image pixel is regarded as a light-emitting source that goes through a synthetic camera system. Thanks to the depth map, we have the geometrical information of the scene so that the point spread function (PSF) can be derived for each pixel more accurately as compared to conventional approaches where only RGB images are involved. Then, we make use of the derived PSFs to solve an optimization so as to reconstruct an all-in-focus image. The reconstructed results are evaluated by comparison with the original all-in-focus images. Compared to other methods for the deblurring of defocused images, our method shows a better recovery of image details.",

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author = "Yiqun Wu and Chao Sun and Bing Zeng and Dehua Xie and Shuaicheng Liu and Xianzhong Chen",

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doi = "10.1109/VCIP.2016.7805485",

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Wu, Y, Sun, C, Zeng, B, Xie, D, Liu, S & Chen, X 2017, Geometry-based PSF estimation and deblurring of defocused images with depth information. in VCIP 2016 - 30th Anniversary of Visual Communication and Image Processing., 7805485, VCIP 2016 - 30th Anniversary of Visual Communication and Image Processing, Institute of Electrical and Electronics Engineers Inc., 2016 IEEE Visual Communication and Image Processing, VCIP 2016, Chengdu, China, 27/11/16. https://doi.org/10.1109/VCIP.2016.7805485

Geometry-based PSF estimation and deblurring of defocused images with depth information. / Wu, Yiqun; Sun, Chao; Zeng, Bing et al.
VCIP 2016 - 30th Anniversary of Visual Communication and Image Processing. Institute of Electrical and Electronics Engineers Inc., 2017. 7805485 (VCIP 2016 - 30th Anniversary of Visual Communication and Image Processing).

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

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AU - Chen, Xianzhong

PY - 2017/1/4

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AB - We propose in this paper an algorithm to recover the blurred details of an image caused by defocusing during the photo-taking. Our algorithm takes one RGB image as well as its depth map as the input. We build up a model in which each captured image pixel is regarded as a light-emitting source that goes through a synthetic camera system. Thanks to the depth map, we have the geometrical information of the scene so that the point spread function (PSF) can be derived for each pixel more accurately as compared to conventional approaches where only RGB images are involved. Then, we make use of the derived PSFs to solve an optimization so as to reconstruct an all-in-focus image. The reconstructed results are evaluated by comparison with the original all-in-focus images. Compared to other methods for the deblurring of defocused images, our method shows a better recovery of image details.

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Wu Y, Sun C, Zeng B, Xie D, Liu S, Chen X. Geometry-based PSF estimation and deblurring of defocused images with depth information. In VCIP 2016 - 30th Anniversary of Visual Communication and Image Processing. Institute of Electrical and Electronics Engineers Inc. 2017. 7805485. (VCIP 2016 - 30th Anniversary of Visual Communication and Image Processing). doi: 10.1109/VCIP.2016.7805485

Geometry-based PSF estimation and deblurring of defocused images with depth information

Abstract

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Bibliographical note

Keywords

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