A single image dehazing model using total variation and inter-channel correlation
Abstract Outdoor images are often degraded by haze, causing a change of image contrast and color values. In this paper, we propose a novel variational model for the removal of haze in a single color image, by incorporating an inter-channel correlation term into the total variation based model in Wan...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Kang, Myeongmin [verfasserIn] |
|---|
| Format: |
Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2019 |
|---|
| Schlagwörter: |
|---|
| Anmerkung: |
© Springer Science+Business Media, LLC, part of Springer Nature 2019 |
|---|
| Übergeordnetes Werk: |
Enthalten in: Multidimensional systems and signal processing - Springer US, 1990, 31(2019), 2 vom: 02. Aug., Seite 431-464 |
|---|---|
| Übergeordnetes Werk: |
volume:31 ; year:2019 ; number:2 ; day:02 ; month:08 ; pages:431-464 |
| Links: |
|---|
| DOI / URN: |
10.1007/s11045-019-00670-7 |
|---|
| Katalog-ID: |
OLC2048111203 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | OLC2048111203 | ||
| 003 | DE-627 | ||
| 005 | 20230504125722.0 | ||
| 007 | tu | ||
| 008 | 200819s2019 xx ||||| 00| ||eng c | ||
| 024 | 7 | |a 10.1007/s11045-019-00670-7 |2 doi | |
| 035 | |a (DE-627)OLC2048111203 | ||
| 035 | |a (DE-He213)s11045-019-00670-7-p | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | 4 | |a 510 |q VZ |
| 100 | 1 | |a Kang, Myeongmin |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a A single image dehazing model using total variation and inter-channel correlation |
| 264 | 1 | |c 2019 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ohne Hilfsmittel zu benutzen |b n |2 rdamedia | ||
| 338 | |a Band |b nc |2 rdacarrier | ||
| 500 | |a © Springer Science+Business Media, LLC, part of Springer Nature 2019 | ||
| 520 | |a Abstract Outdoor images are often degraded by haze, causing a change of image contrast and color values. In this paper, we propose a novel variational model for the removal of haze in a single color image, by incorporating an inter-channel correlation term into the total variation based model in Wang et al. (Pattern Recognit 80:196–209, 2018). The proposed model enables both color and gray-valued transmission maps, contributing to its broad applications, and its convergence analysis is also provided. To realize the proposed model, we adopt an alternating minimization algorithm, and then the alternating direction method of multipliers is employed for solving subproblems. These result in an efficient iterative algorithm, with its convergence proven. Numerical experiments validate the outstanding performance of the proposed model compared to the state-of-the-art methods. | ||
| 650 | 4 | |a Single image dehazing | |
| 650 | 4 | |a Variational model | |
| 650 | 4 | |a Total variation | |
| 650 | 4 | |a Inter-channel correlation | |
| 650 | 4 | |a Alternating minimization | |
| 700 | 1 | |a Jung, Miyoun |0 (orcid)0000-0001-7370-6651 |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Multidimensional systems and signal processing |d Springer US, 1990 |g 31(2019), 2 vom: 02. Aug., Seite 431-464 |w (DE-627)130892076 |w (DE-600)1041098-3 |w (DE-576)038686074 |x 0923-6082 |7 nnns |
| 773 | 1 | 8 | |g volume:31 |g year:2019 |g number:2 |g day:02 |g month:08 |g pages:431-464 |
| 856 | 4 | 1 | |u https://doi.org/10.1007/s11045-019-00670-7 |z lizenzpflichtig |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a SYSFLAG_A | ||
| 912 | |a GBV_OLC | ||
| 912 | |a SSG-OLC-MAT | ||
| 912 | |a SSG-OPC-MAT | ||
| 912 | |a GBV_ILN_70 | ||
| 951 | |a AR | ||
| 952 | |d 31 |j 2019 |e 2 |b 02 |c 08 |h 431-464 | ||
| author_variant |
m k mk m j mj |
|---|---|
| matchkey_str |
article:09236082:2019----::snliaeeaigoeuigoavrainnit |
| hierarchy_sort_str |
2019 |
| publishDate |
2019 |
| allfields |
10.1007/s11045-019-00670-7 doi (DE-627)OLC2048111203 (DE-He213)s11045-019-00670-7-p DE-627 ger DE-627 rakwb eng 510 VZ Kang, Myeongmin verfasserin aut A single image dehazing model using total variation and inter-channel correlation 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract Outdoor images are often degraded by haze, causing a change of image contrast and color values. In this paper, we propose a novel variational model for the removal of haze in a single color image, by incorporating an inter-channel correlation term into the total variation based model in Wang et al. (Pattern Recognit 80:196–209, 2018). The proposed model enables both color and gray-valued transmission maps, contributing to its broad applications, and its convergence analysis is also provided. To realize the proposed model, we adopt an alternating minimization algorithm, and then the alternating direction method of multipliers is employed for solving subproblems. These result in an efficient iterative algorithm, with its convergence proven. Numerical experiments validate the outstanding performance of the proposed model compared to the state-of-the-art methods. Single image dehazing Variational model Total variation Inter-channel correlation Alternating minimization Jung, Miyoun (orcid)0000-0001-7370-6651 aut Enthalten in Multidimensional systems and signal processing Springer US, 1990 31(2019), 2 vom: 02. Aug., Seite 431-464 (DE-627)130892076 (DE-600)1041098-3 (DE-576)038686074 0923-6082 nnns volume:31 year:2019 number:2 day:02 month:08 pages:431-464 https://doi.org/10.1007/s11045-019-00670-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 AR 31 2019 2 02 08 431-464 |
| spelling |
10.1007/s11045-019-00670-7 doi (DE-627)OLC2048111203 (DE-He213)s11045-019-00670-7-p DE-627 ger DE-627 rakwb eng 510 VZ Kang, Myeongmin verfasserin aut A single image dehazing model using total variation and inter-channel correlation 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract Outdoor images are often degraded by haze, causing a change of image contrast and color values. In this paper, we propose a novel variational model for the removal of haze in a single color image, by incorporating an inter-channel correlation term into the total variation based model in Wang et al. (Pattern Recognit 80:196–209, 2018). The proposed model enables both color and gray-valued transmission maps, contributing to its broad applications, and its convergence analysis is also provided. To realize the proposed model, we adopt an alternating minimization algorithm, and then the alternating direction method of multipliers is employed for solving subproblems. These result in an efficient iterative algorithm, with its convergence proven. Numerical experiments validate the outstanding performance of the proposed model compared to the state-of-the-art methods. Single image dehazing Variational model Total variation Inter-channel correlation Alternating minimization Jung, Miyoun (orcid)0000-0001-7370-6651 aut Enthalten in Multidimensional systems and signal processing Springer US, 1990 31(2019), 2 vom: 02. Aug., Seite 431-464 (DE-627)130892076 (DE-600)1041098-3 (DE-576)038686074 0923-6082 nnns volume:31 year:2019 number:2 day:02 month:08 pages:431-464 https://doi.org/10.1007/s11045-019-00670-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 AR 31 2019 2 02 08 431-464 |
| allfields_unstemmed |
10.1007/s11045-019-00670-7 doi (DE-627)OLC2048111203 (DE-He213)s11045-019-00670-7-p DE-627 ger DE-627 rakwb eng 510 VZ Kang, Myeongmin verfasserin aut A single image dehazing model using total variation and inter-channel correlation 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract Outdoor images are often degraded by haze, causing a change of image contrast and color values. In this paper, we propose a novel variational model for the removal of haze in a single color image, by incorporating an inter-channel correlation term into the total variation based model in Wang et al. (Pattern Recognit 80:196–209, 2018). The proposed model enables both color and gray-valued transmission maps, contributing to its broad applications, and its convergence analysis is also provided. To realize the proposed model, we adopt an alternating minimization algorithm, and then the alternating direction method of multipliers is employed for solving subproblems. These result in an efficient iterative algorithm, with its convergence proven. Numerical experiments validate the outstanding performance of the proposed model compared to the state-of-the-art methods. Single image dehazing Variational model Total variation Inter-channel correlation Alternating minimization Jung, Miyoun (orcid)0000-0001-7370-6651 aut Enthalten in Multidimensional systems and signal processing Springer US, 1990 31(2019), 2 vom: 02. Aug., Seite 431-464 (DE-627)130892076 (DE-600)1041098-3 (DE-576)038686074 0923-6082 nnns volume:31 year:2019 number:2 day:02 month:08 pages:431-464 https://doi.org/10.1007/s11045-019-00670-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 AR 31 2019 2 02 08 431-464 |
| allfieldsGer |
10.1007/s11045-019-00670-7 doi (DE-627)OLC2048111203 (DE-He213)s11045-019-00670-7-p DE-627 ger DE-627 rakwb eng 510 VZ Kang, Myeongmin verfasserin aut A single image dehazing model using total variation and inter-channel correlation 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract Outdoor images are often degraded by haze, causing a change of image contrast and color values. In this paper, we propose a novel variational model for the removal of haze in a single color image, by incorporating an inter-channel correlation term into the total variation based model in Wang et al. (Pattern Recognit 80:196–209, 2018). The proposed model enables both color and gray-valued transmission maps, contributing to its broad applications, and its convergence analysis is also provided. To realize the proposed model, we adopt an alternating minimization algorithm, and then the alternating direction method of multipliers is employed for solving subproblems. These result in an efficient iterative algorithm, with its convergence proven. Numerical experiments validate the outstanding performance of the proposed model compared to the state-of-the-art methods. Single image dehazing Variational model Total variation Inter-channel correlation Alternating minimization Jung, Miyoun (orcid)0000-0001-7370-6651 aut Enthalten in Multidimensional systems and signal processing Springer US, 1990 31(2019), 2 vom: 02. Aug., Seite 431-464 (DE-627)130892076 (DE-600)1041098-3 (DE-576)038686074 0923-6082 nnns volume:31 year:2019 number:2 day:02 month:08 pages:431-464 https://doi.org/10.1007/s11045-019-00670-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 AR 31 2019 2 02 08 431-464 |
| allfieldsSound |
10.1007/s11045-019-00670-7 doi (DE-627)OLC2048111203 (DE-He213)s11045-019-00670-7-p DE-627 ger DE-627 rakwb eng 510 VZ Kang, Myeongmin verfasserin aut A single image dehazing model using total variation and inter-channel correlation 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract Outdoor images are often degraded by haze, causing a change of image contrast and color values. In this paper, we propose a novel variational model for the removal of haze in a single color image, by incorporating an inter-channel correlation term into the total variation based model in Wang et al. (Pattern Recognit 80:196–209, 2018). The proposed model enables both color and gray-valued transmission maps, contributing to its broad applications, and its convergence analysis is also provided. To realize the proposed model, we adopt an alternating minimization algorithm, and then the alternating direction method of multipliers is employed for solving subproblems. These result in an efficient iterative algorithm, with its convergence proven. Numerical experiments validate the outstanding performance of the proposed model compared to the state-of-the-art methods. Single image dehazing Variational model Total variation Inter-channel correlation Alternating minimization Jung, Miyoun (orcid)0000-0001-7370-6651 aut Enthalten in Multidimensional systems and signal processing Springer US, 1990 31(2019), 2 vom: 02. Aug., Seite 431-464 (DE-627)130892076 (DE-600)1041098-3 (DE-576)038686074 0923-6082 nnns volume:31 year:2019 number:2 day:02 month:08 pages:431-464 https://doi.org/10.1007/s11045-019-00670-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 AR 31 2019 2 02 08 431-464 |
| language |
English |
| source |
Enthalten in Multidimensional systems and signal processing 31(2019), 2 vom: 02. Aug., Seite 431-464 volume:31 year:2019 number:2 day:02 month:08 pages:431-464 |
| sourceStr |
Enthalten in Multidimensional systems and signal processing 31(2019), 2 vom: 02. Aug., Seite 431-464 volume:31 year:2019 number:2 day:02 month:08 pages:431-464 |
| format_phy_str_mv |
Article |
| institution |
findex.gbv.de |
| topic_facet |
Single image dehazing Variational model Total variation Inter-channel correlation Alternating minimization |
| dewey-raw |
510 |
| isfreeaccess_bool |
false |
| container_title |
Multidimensional systems and signal processing |
| authorswithroles_txt_mv |
Kang, Myeongmin @@aut@@ Jung, Miyoun @@aut@@ |
| publishDateDaySort_date |
2019-08-02T00:00:00Z |
| hierarchy_top_id |
130892076 |
| dewey-sort |
3510 |
| id |
OLC2048111203 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC2048111203</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230504125722.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200819s2019 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s11045-019-00670-7</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2048111203</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s11045-019-00670-7-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">510</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Kang, Myeongmin</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">A single image dehazing model using total variation and inter-channel correlation</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2019</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer Science+Business Media, LLC, part of Springer Nature 2019</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Outdoor images are often degraded by haze, causing a change of image contrast and color values. In this paper, we propose a novel variational model for the removal of haze in a single color image, by incorporating an inter-channel correlation term into the total variation based model in Wang et al. (Pattern Recognit 80:196–209, 2018). The proposed model enables both color and gray-valued transmission maps, contributing to its broad applications, and its convergence analysis is also provided. To realize the proposed model, we adopt an alternating minimization algorithm, and then the alternating direction method of multipliers is employed for solving subproblems. These result in an efficient iterative algorithm, with its convergence proven. Numerical experiments validate the outstanding performance of the proposed model compared to the state-of-the-art methods.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Single image dehazing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Variational model</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Total variation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Inter-channel correlation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Alternating minimization</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Jung, Miyoun</subfield><subfield code="0">(orcid)0000-0001-7370-6651</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Multidimensional systems and signal processing</subfield><subfield code="d">Springer US, 1990</subfield><subfield code="g">31(2019), 2 vom: 02. Aug., Seite 431-464</subfield><subfield code="w">(DE-627)130892076</subfield><subfield code="w">(DE-600)1041098-3</subfield><subfield code="w">(DE-576)038686074</subfield><subfield code="x">0923-6082</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:31</subfield><subfield code="g">year:2019</subfield><subfield code="g">number:2</subfield><subfield code="g">day:02</subfield><subfield code="g">month:08</subfield><subfield code="g">pages:431-464</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.1007/s11045-019-00670-7</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OPC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">31</subfield><subfield code="j">2019</subfield><subfield code="e">2</subfield><subfield code="b">02</subfield><subfield code="c">08</subfield><subfield code="h">431-464</subfield></datafield></record></collection>
|
| author |
Kang, Myeongmin |
| spellingShingle |
Kang, Myeongmin ddc 510 misc Single image dehazing misc Variational model misc Total variation misc Inter-channel correlation misc Alternating minimization A single image dehazing model using total variation and inter-channel correlation |
| authorStr |
Kang, Myeongmin |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)130892076 |
| format |
Article |
| dewey-ones |
510 - Mathematics |
| delete_txt_mv |
keep |
| author_role |
aut aut |
| collection |
OLC |
| remote_str |
false |
| illustrated |
Not Illustrated |
| issn |
0923-6082 |
| topic_title |
510 VZ A single image dehazing model using total variation and inter-channel correlation Single image dehazing Variational model Total variation Inter-channel correlation Alternating minimization |
| topic |
ddc 510 misc Single image dehazing misc Variational model misc Total variation misc Inter-channel correlation misc Alternating minimization |
| topic_unstemmed |
ddc 510 misc Single image dehazing misc Variational model misc Total variation misc Inter-channel correlation misc Alternating minimization |
| topic_browse |
ddc 510 misc Single image dehazing misc Variational model misc Total variation misc Inter-channel correlation misc Alternating minimization |
| format_facet |
Aufsätze Gedruckte Aufsätze |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
nc |
| hierarchy_parent_title |
Multidimensional systems and signal processing |
| hierarchy_parent_id |
130892076 |
| dewey-tens |
510 - Mathematics |
| hierarchy_top_title |
Multidimensional systems and signal processing |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)130892076 (DE-600)1041098-3 (DE-576)038686074 |
| title |
A single image dehazing model using total variation and inter-channel correlation |
| ctrlnum |
(DE-627)OLC2048111203 (DE-He213)s11045-019-00670-7-p |
| title_full |
A single image dehazing model using total variation and inter-channel correlation |
| author_sort |
Kang, Myeongmin |
| journal |
Multidimensional systems and signal processing |
| journalStr |
Multidimensional systems and signal processing |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
500 - Science |
| recordtype |
marc |
| publishDateSort |
2019 |
| contenttype_str_mv |
txt |
| container_start_page |
431 |
| author_browse |
Kang, Myeongmin Jung, Miyoun |
| container_volume |
31 |
| class |
510 VZ |
| format_se |
Aufsätze |
| author-letter |
Kang, Myeongmin |
| doi_str_mv |
10.1007/s11045-019-00670-7 |
| normlink |
(ORCID)0000-0001-7370-6651 |
| normlink_prefix_str_mv |
(orcid)0000-0001-7370-6651 |
| dewey-full |
510 |
| title_sort |
a single image dehazing model using total variation and inter-channel correlation |
| title_auth |
A single image dehazing model using total variation and inter-channel correlation |
| abstract |
Abstract Outdoor images are often degraded by haze, causing a change of image contrast and color values. In this paper, we propose a novel variational model for the removal of haze in a single color image, by incorporating an inter-channel correlation term into the total variation based model in Wang et al. (Pattern Recognit 80:196–209, 2018). The proposed model enables both color and gray-valued transmission maps, contributing to its broad applications, and its convergence analysis is also provided. To realize the proposed model, we adopt an alternating minimization algorithm, and then the alternating direction method of multipliers is employed for solving subproblems. These result in an efficient iterative algorithm, with its convergence proven. Numerical experiments validate the outstanding performance of the proposed model compared to the state-of-the-art methods. © Springer Science+Business Media, LLC, part of Springer Nature 2019 |
| abstractGer |
Abstract Outdoor images are often degraded by haze, causing a change of image contrast and color values. In this paper, we propose a novel variational model for the removal of haze in a single color image, by incorporating an inter-channel correlation term into the total variation based model in Wang et al. (Pattern Recognit 80:196–209, 2018). The proposed model enables both color and gray-valued transmission maps, contributing to its broad applications, and its convergence analysis is also provided. To realize the proposed model, we adopt an alternating minimization algorithm, and then the alternating direction method of multipliers is employed for solving subproblems. These result in an efficient iterative algorithm, with its convergence proven. Numerical experiments validate the outstanding performance of the proposed model compared to the state-of-the-art methods. © Springer Science+Business Media, LLC, part of Springer Nature 2019 |
| abstract_unstemmed |
Abstract Outdoor images are often degraded by haze, causing a change of image contrast and color values. In this paper, we propose a novel variational model for the removal of haze in a single color image, by incorporating an inter-channel correlation term into the total variation based model in Wang et al. (Pattern Recognit 80:196–209, 2018). The proposed model enables both color and gray-valued transmission maps, contributing to its broad applications, and its convergence analysis is also provided. To realize the proposed model, we adopt an alternating minimization algorithm, and then the alternating direction method of multipliers is employed for solving subproblems. These result in an efficient iterative algorithm, with its convergence proven. Numerical experiments validate the outstanding performance of the proposed model compared to the state-of-the-art methods. © Springer Science+Business Media, LLC, part of Springer Nature 2019 |
| collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OPC-MAT GBV_ILN_70 |
| container_issue |
2 |
| title_short |
A single image dehazing model using total variation and inter-channel correlation |
| url |
https://doi.org/10.1007/s11045-019-00670-7 |
| remote_bool |
false |
| author2 |
Jung, Miyoun |
| author2Str |
Jung, Miyoun |
| ppnlink |
130892076 |
| mediatype_str_mv |
n |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| doi_str |
10.1007/s11045-019-00670-7 |
| up_date |
2024-07-03T17:34:41.646Z |
| _version_ |
1803580165745278976 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC2048111203</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230504125722.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200819s2019 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s11045-019-00670-7</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2048111203</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s11045-019-00670-7-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">510</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Kang, Myeongmin</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">A single image dehazing model using total variation and inter-channel correlation</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2019</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer Science+Business Media, LLC, part of Springer Nature 2019</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Outdoor images are often degraded by haze, causing a change of image contrast and color values. In this paper, we propose a novel variational model for the removal of haze in a single color image, by incorporating an inter-channel correlation term into the total variation based model in Wang et al. (Pattern Recognit 80:196–209, 2018). The proposed model enables both color and gray-valued transmission maps, contributing to its broad applications, and its convergence analysis is also provided. To realize the proposed model, we adopt an alternating minimization algorithm, and then the alternating direction method of multipliers is employed for solving subproblems. These result in an efficient iterative algorithm, with its convergence proven. Numerical experiments validate the outstanding performance of the proposed model compared to the state-of-the-art methods.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Single image dehazing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Variational model</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Total variation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Inter-channel correlation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Alternating minimization</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Jung, Miyoun</subfield><subfield code="0">(orcid)0000-0001-7370-6651</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Multidimensional systems and signal processing</subfield><subfield code="d">Springer US, 1990</subfield><subfield code="g">31(2019), 2 vom: 02. Aug., Seite 431-464</subfield><subfield code="w">(DE-627)130892076</subfield><subfield code="w">(DE-600)1041098-3</subfield><subfield code="w">(DE-576)038686074</subfield><subfield code="x">0923-6082</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:31</subfield><subfield code="g">year:2019</subfield><subfield code="g">number:2</subfield><subfield code="g">day:02</subfield><subfield code="g">month:08</subfield><subfield code="g">pages:431-464</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.1007/s11045-019-00670-7</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OPC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">31</subfield><subfield code="j">2019</subfield><subfield code="e">2</subfield><subfield code="b">02</subfield><subfield code="c">08</subfield><subfield code="h">431-464</subfield></datafield></record></collection>
|
| score |
7.400487 |