Single image haze removal based on global-local optimization for depth map

Hongda Zhang; Yuanyuan Gao; Hai Miao Hu; Qiang Guo; Yukun Cui

doi:10.1007/978-3-319-77380-3_12

Single image haze removal based on global-local optimization for depth map

Hongda Zhang
, Yuanyuan Gao
, Hai Miao Hu^*
, Qiang Guo
, Yukun Cui

^*Corresponding author for this work

School of Computer Science and Engineering

Beihang University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

With the wide application of computer vision system, image haze removal has become a new challenge. A great number of image dehazing methods are proposed, which have varying degrees of dehazing effects and different shortcomings. The color attenuation prior for image haze removal presents a new way based on depth map estimation. The novel method performs well with little distortion and natural colors. This paper discusses the color attenuation prior for image haze removal and proposes the haze removal method based on global-local optimization for depth map. Regarding the halo artifacts in dehazing images, we combine the minimum filter and minimum-maximum filter to detect the potential areas of the halo artifacts and suppress them. For the case of the underestimation of depth information, we take advantage of the atmospheric light estimation to perform global optimization for final depth map. Experimental results demonstrate excellent performance of the proposed method.

Original language	English
Title of host publication	Advances in Multimedia Information Processing – PCM 2017 - 18th Pacific-Rim Conference on Multimedia, Revised Selected Papers
Editors	Bing Zeng, Hongliang Li, Abdulmotaleb El Saddik, Xiaopeng Fan, Shuqiang Jiang, Qingming Huang
Publisher	Springer Verlag
Pages	117-127
Number of pages	11
ISBN (Print)	9783319773797
DOIs	https://doi.org/10.1007/978-3-319-77380-3_12
State	Published - 2018
Event	18th Pacific-Rim Conference on Multimedia, PCM 2017 - Harbin, China Duration: 28 Sep 2017 → 29 Sep 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10735 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	18th Pacific-Rim Conference on Multimedia, PCM 2017
Country/Territory	China
City	Harbin
Period	28/09/17 → 29/09/17

Keywords

Depth map
Global-local optimization
Image haze removal
Minimum-Maximum filter

Access to Document

10.1007/978-3-319-77380-3_12

Cite this

Zhang, H., Gao, Y., Hu, H. M., Guo, Q., & Cui, Y. (2018). Single image haze removal based on global-local optimization for depth map. In B. Zeng, H. Li, A. El Saddik, X. Fan, S. Jiang, & Q. Huang (Eds.), Advances in Multimedia Information Processing – PCM 2017 - 18th Pacific-Rim Conference on Multimedia, Revised Selected Papers (pp. 117-127). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10735 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-77380-3_12

Zhang, Hongda ; Gao, Yuanyuan ; Hu, Hai Miao et al. / Single image haze removal based on global-local optimization for depth map. Advances in Multimedia Information Processing – PCM 2017 - 18th Pacific-Rim Conference on Multimedia, Revised Selected Papers. editor / Bing Zeng ; Hongliang Li ; Abdulmotaleb El Saddik ; Xiaopeng Fan ; Shuqiang Jiang ; Qingming Huang. Springer Verlag, 2018. pp. 117-127 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{7be9fb50432942f98a6b024302217abe,

title = "Single image haze removal based on global-local optimization for depth map",

abstract = "With the wide application of computer vision system, image haze removal has become a new challenge. A great number of image dehazing methods are proposed, which have varying degrees of dehazing effects and different shortcomings. The color attenuation prior for image haze removal presents a new way based on depth map estimation. The novel method performs well with little distortion and natural colors. This paper discusses the color attenuation prior for image haze removal and proposes the haze removal method based on global-local optimization for depth map. Regarding the halo artifacts in dehazing images, we combine the minimum filter and minimum-maximum filter to detect the potential areas of the halo artifacts and suppress them. For the case of the underestimation of depth information, we take advantage of the atmospheric light estimation to perform global optimization for final depth map. Experimental results demonstrate excellent performance of the proposed method.",

keywords = "Depth map, Global-local optimization, Image haze removal, Minimum-Maximum filter",

author = "Hongda Zhang and Yuanyuan Gao and Hu, \{Hai Miao\} and Qiang Guo and Yukun Cui",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG, part of Springer Nature 2018.; 18th Pacific-Rim Conference on Multimedia, PCM 2017 ; Conference date: 28-09-2017 Through 29-09-2017",

year = "2018",

doi = "10.1007/978-3-319-77380-3\_12",

language = "英语",

isbn = "9783319773797",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "117--127",

editor = "Bing Zeng and Hongliang Li and \{El Saddik\}, Abdulmotaleb and Xiaopeng Fan and Shuqiang Jiang and Qingming Huang",

booktitle = "Advances in Multimedia Information Processing – PCM 2017 - 18th Pacific-Rim Conference on Multimedia, Revised Selected Papers",

address = "德国",

}

Zhang, H, Gao, Y, Hu, HM, Guo, Q & Cui, Y 2018, Single image haze removal based on global-local optimization for depth map. in B Zeng, H Li, A El Saddik, X Fan, S Jiang & Q Huang (eds), Advances in Multimedia Information Processing – PCM 2017 - 18th Pacific-Rim Conference on Multimedia, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10735 LNCS, Springer Verlag, pp. 117-127, 18th Pacific-Rim Conference on Multimedia, PCM 2017, Harbin, China, 28/09/17. https://doi.org/10.1007/978-3-319-77380-3_12

Single image haze removal based on global-local optimization for depth map. / Zhang, Hongda; Gao, Yuanyuan; Hu, Hai Miao et al.
Advances in Multimedia Information Processing – PCM 2017 - 18th Pacific-Rim Conference on Multimedia, Revised Selected Papers. ed. / Bing Zeng; Hongliang Li; Abdulmotaleb El Saddik; Xiaopeng Fan; Shuqiang Jiang; Qingming Huang. Springer Verlag, 2018. p. 117-127 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10735 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Single image haze removal based on global-local optimization for depth map

AU - Zhang, Hongda

AU - Gao, Yuanyuan

AU - Hu, Hai Miao

AU - Guo, Qiang

AU - Cui, Yukun

N1 - Publisher Copyright: © Springer International Publishing AG, part of Springer Nature 2018.

PY - 2018

Y1 - 2018

N2 - With the wide application of computer vision system, image haze removal has become a new challenge. A great number of image dehazing methods are proposed, which have varying degrees of dehazing effects and different shortcomings. The color attenuation prior for image haze removal presents a new way based on depth map estimation. The novel method performs well with little distortion and natural colors. This paper discusses the color attenuation prior for image haze removal and proposes the haze removal method based on global-local optimization for depth map. Regarding the halo artifacts in dehazing images, we combine the minimum filter and minimum-maximum filter to detect the potential areas of the halo artifacts and suppress them. For the case of the underestimation of depth information, we take advantage of the atmospheric light estimation to perform global optimization for final depth map. Experimental results demonstrate excellent performance of the proposed method.

AB - With the wide application of computer vision system, image haze removal has become a new challenge. A great number of image dehazing methods are proposed, which have varying degrees of dehazing effects and different shortcomings. The color attenuation prior for image haze removal presents a new way based on depth map estimation. The novel method performs well with little distortion and natural colors. This paper discusses the color attenuation prior for image haze removal and proposes the haze removal method based on global-local optimization for depth map. Regarding the halo artifacts in dehazing images, we combine the minimum filter and minimum-maximum filter to detect the potential areas of the halo artifacts and suppress them. For the case of the underestimation of depth information, we take advantage of the atmospheric light estimation to perform global optimization for final depth map. Experimental results demonstrate excellent performance of the proposed method.

KW - Depth map

KW - Global-local optimization

KW - Image haze removal

KW - Minimum-Maximum filter

UR - https://www.scopus.com/pages/publications/85047489903

U2 - 10.1007/978-3-319-77380-3_12

DO - 10.1007/978-3-319-77380-3_12

M3 - 会议稿件

AN - SCOPUS:85047489903

SN - 9783319773797

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 117

EP - 127

BT - Advances in Multimedia Information Processing – PCM 2017 - 18th Pacific-Rim Conference on Multimedia, Revised Selected Papers

A2 - Zeng, Bing

A2 - Li, Hongliang

A2 - El Saddik, Abdulmotaleb

A2 - Fan, Xiaopeng

A2 - Jiang, Shuqiang

A2 - Huang, Qingming

PB - Springer Verlag

T2 - 18th Pacific-Rim Conference on Multimedia, PCM 2017

Y2 - 28 September 2017 through 29 September 2017

ER -

Zhang H, Gao Y, Hu HM, Guo Q, Cui Y. Single image haze removal based on global-local optimization for depth map. In Zeng B, Li H, El Saddik A, Fan X, Jiang S, Huang Q, editors, Advances in Multimedia Information Processing – PCM 2017 - 18th Pacific-Rim Conference on Multimedia, Revised Selected Papers. Springer Verlag. 2018. p. 117-127. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-77380-3_12

Single image haze removal based on global-local optimization for depth map

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