Reconstruction of catadioptric omnidirectional images using dual alternating total variation minimization View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-11-09

AUTHORS

Soraya Zenati, Abdelhani Boukrouche, Larbi Boubchir

ABSTRACT

This paper discusses the possibility to extend and apply the conventional two dimensional recovering images from blurry and noisy observation with the total variation regularization method to the catadioptric images. The principal in this special method is the stabilization of dual alternating minimization. The latter introduces two auxiliary half quadratic variables to transfer the system out of the ill-posed term. The main contribution of this paper is the use of the inverse stereographic projection and the spherical harmonics in order to adapt this proposed deconvolution with catadioptric omnidirectional images. The projection on the unit sphere of the omnidirectional image, is one way to alleviate the problem of the heterogeneous resolution and the negative effects of anamorphosis. In both anisotropic and isotropic deconvolutions, the experimental results conducted on synthetic as well as captured catadioptric omnidirectional images which are subject to various effects, confirm the performance of the proposed method to restore such images impaired by the blur and noise. Compared with several state-of-the-art approaches, the images resulted can achieve up to an acceptable and higher level of deconvolution quality. More... »

PAGES

1-17

References to SciGraph publications

  • 2018-01-26. Fuzzy Logic Controller with Color Vision System Tracking for Mobile Manipulator Robot in THE INTERNATIONAL CONFERENCE ON ADVANCED MACHINE LEARNING TECHNOLOGIES AND APPLICATIONS (AMLTA2018)
  • 1997-04. Image recovery via total variation minimization and related problems in NUMERISCHE MATHEMATIK
  • 2001-12. Catadioptric Projective Geometry in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2013-01. Generating near-spherical range panoramas by fusing optical flow and stereo from a single-camera folded catadioptric rig in MACHINE VISION AND APPLICATIONS
  • 2014-08. Extrinsic calibration of heterogeneous cameras by line images in MACHINE VISION AND APPLICATIONS
  • 2013-04. Markerless tracking and gesture recognition using polar correlation of camera optical flow in MACHINE VISION AND APPLICATIONS
  • 2018. Development of an Android System Integrated with Sensor Networks in GEMINOID STUDIES
  • 2013-05. Hybrid homographies and fundamental matrices mixing uncalibrated omnidirectional and conventional cameras in MACHINE VISION AND APPLICATIONS
  • 2012-01. Vision Based UAV Attitude Estimation: Progress and Insights in JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
  • 2013-04. Panoramic Gaussian Mixture Model and large-scale range background substraction method for PTZ camera-based surveillance systems in MACHINE VISION AND APPLICATIONS
  • 2003-07. FFTs for the 2-Sphere-Improvements and Variations in JOURNAL OF FOURIER ANALYSIS AND APPLICATIONS
  • 2012-07. Efficient omni-image unwarping using geometric symmetry in MACHINE VISION AND APPLICATIONS
  • 2017-11. Accelerated Alternating Descent Methods for Dykstra-Like Problems in JOURNAL OF MATHEMATICAL IMAGING AND VISION
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s12530-018-9257-5

    DOI

    http://dx.doi.org/10.1007/s12530-018-9257-5

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1109794221


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0801", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Artificial Intelligence and Image Processing", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Information and Computing Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Badji Mokhtar University", 
              "id": "https://www.grid.ac/institutes/grid.440473.0", 
              "name": [
                "Laboratory of Inverse Problems, Modelling, Information and Systems, University 8 Mai 1945 Guelma, PO Box 401, 24000, Guelma, Algeria", 
                "Department of Computer Sciences, Badji Mokhtar University, PO Box 12, 23000, Annaba, Algeria"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Zenati", 
            "givenName": "Soraya", 
            "id": "sg:person.014030375003.86", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014030375003.86"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Universit\u00e9 8 mai 1945 Guelma", 
              "id": "https://www.grid.ac/institutes/grid.442444.6", 
              "name": [
                "Laboratory of Inverse Problems, Modelling, Information and Systems, University 8 Mai 1945 Guelma, PO Box 401, 24000, Guelma, Algeria"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Boukrouche", 
            "givenName": "Abdelhani", 
            "id": "sg:person.013612572172.43", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013612572172.43"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Paris 8 University", 
              "id": "https://www.grid.ac/institutes/grid.15878.33", 
              "name": [
                "LIASD research Lab., University of Paris 8, 2 rue de la Libert\u00e9, 93526, Saint-Denis, France"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Boubchir", 
            "givenName": "Larbi", 
            "id": "sg:person.014157217771.40", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014157217771.40"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1007/s00041-003-0018-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005843436", 
              "https://doi.org/10.1007/s00041-003-0018-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1023/a:1013610201135", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005871774", 
              "https://doi.org/10.1023/a:1013610201135"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1006/aama.1994.1008", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007481173"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevd.63.123002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008827496"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevd.63.123002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008827496"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00138-014-0624-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017113095", 
              "https://doi.org/10.1007/s00138-014-0624-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ijleo.2013.05.146", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017442585"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ijleo.2014.01.068", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022792398"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00138-010-0312-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1030196889", 
              "https://doi.org/10.1007/s00138-010-0312-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00138-010-0312-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1030196889", 
              "https://doi.org/10.1007/s00138-010-0312-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0167-2789(92)90242-f", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1030232634"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0167-2789(92)90242-f", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1030232634"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s002110050258", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1030690016", 
              "https://doi.org/10.1007/s002110050258"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00138-012-0451-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031372258", 
              "https://doi.org/10.1007/s00138-012-0451-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/09500340.2013.787465", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033860978"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00138-012-0424-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044717250", 
              "https://doi.org/10.1007/s00138-012-0424-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10846-011-9588-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050678333", 
              "https://doi.org/10.1007/s10846-011-9588-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ultramic.2016.12.020", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051571172"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00138-012-0426-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051764940", 
              "https://doi.org/10.1007/s00138-012-0426-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00138-011-0368-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052885626", 
              "https://doi.org/10.1007/s00138-011-0368-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1049/iet-ipr.2013.0330", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1056829245"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/lsp.2007.906221", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061377065"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tip.2003.819861", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061640964"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/tsp.2016.2645510", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061806034"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1137/080724265", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1062854762"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1137/s1064827596299767", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1062884404"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10851-017-0724-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1084027243", 
              "https://doi.org/10.1007/s10851-017-0724-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10851-017-0724-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1084027243", 
              "https://doi.org/10.1007/s10851-017-0724-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1142/9789812709066_0003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1088727854"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/have.2005.1545652", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1093315520"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/ipta.2012.6469552", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1093389842"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/omnvis.2002.1044483", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1094135591"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/ipta.2015.7367112", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1094308854"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/icip.1994.413269", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1094806947"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/robot.2003.1241653", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1095327818"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/icassp.1996.543670", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1095467643"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/icip.2005.1530011", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1095703294"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/13682199.2017.1408254", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1099696866"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1115/1.4039098", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1100649936"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-319-74690-6_14", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1100657694", 
              "https://doi.org/10.1007/978-3-319-74690-6_14"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-319-74690-6_14", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1100657694", 
              "https://doi.org/10.1007/978-3-319-74690-6_14"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3390/s18020408", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1100754350"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-981-10-8702-8_1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1103671522", 
              "https://doi.org/10.1007/978-981-10-8702-8_1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1364/ao.57.006781", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1106028680"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2018-11-09", 
        "datePublishedReg": "2018-11-09", 
        "description": "This paper discusses the possibility to extend and apply the conventional two dimensional recovering images from blurry and noisy observation with the total variation regularization method to the catadioptric images. The principal in this special method is the stabilization of dual alternating minimization. The latter introduces two auxiliary half quadratic variables to transfer the system out of the ill-posed term. The main contribution of this paper is the use of the inverse stereographic projection and the spherical harmonics in order to adapt this proposed deconvolution with catadioptric omnidirectional images. The projection on the unit sphere of the omnidirectional image, is one way to alleviate the problem of the heterogeneous resolution and the negative effects of anamorphosis. In both anisotropic and isotropic deconvolutions, the experimental results conducted on synthetic as well as captured catadioptric omnidirectional images which are subject to various effects, confirm the performance of the proposed method to restore such images impaired by the blur and noise. Compared with several state-of-the-art approaches, the images resulted can achieve up to an acceptable and higher level of deconvolution quality.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/s12530-018-9257-5", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1136668", 
            "issn": [
              "1868-6478", 
              "1868-6486"
            ], 
            "name": "Evolving Systems", 
            "type": "Periodical"
          }
        ], 
        "name": "Reconstruction of catadioptric omnidirectional images using dual alternating total variation minimization", 
        "pagination": "1-17", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "71384f989bbbefae1dadb82ed16f847e70b8ee51fc951bfdfabb901f2496c821"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s12530-018-9257-5"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1109794221"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s12530-018-9257-5", 
          "https://app.dimensions.ai/details/publication/pub.1109794221"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-10T21:56", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8687_00000610.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://link.springer.com/10.1007%2Fs12530-018-9257-5"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s12530-018-9257-5'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s12530-018-9257-5'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s12530-018-9257-5'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s12530-018-9257-5'


     

    This table displays all metadata directly associated to this object as RDF triples.

    206 TRIPLES      21 PREDICATES      63 URIs      16 LITERALS      5 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s12530-018-9257-5 schema:about anzsrc-for:08
    2 anzsrc-for:0801
    3 schema:author Nefbe39ed0c5d48618f1bb7831183a428
    4 schema:citation sg:pub.10.1007/978-3-319-74690-6_14
    5 sg:pub.10.1007/978-981-10-8702-8_1
    6 sg:pub.10.1007/s00041-003-0018-9
    7 sg:pub.10.1007/s00138-010-0312-x
    8 sg:pub.10.1007/s00138-011-0368-2
    9 sg:pub.10.1007/s00138-012-0424-6
    10 sg:pub.10.1007/s00138-012-0426-4
    11 sg:pub.10.1007/s00138-012-0451-3
    12 sg:pub.10.1007/s00138-014-0624-3
    13 sg:pub.10.1007/s002110050258
    14 sg:pub.10.1007/s10846-011-9588-y
    15 sg:pub.10.1007/s10851-017-0724-6
    16 sg:pub.10.1023/a:1013610201135
    17 https://doi.org/10.1006/aama.1994.1008
    18 https://doi.org/10.1016/0167-2789(92)90242-f
    19 https://doi.org/10.1016/j.ijleo.2013.05.146
    20 https://doi.org/10.1016/j.ijleo.2014.01.068
    21 https://doi.org/10.1016/j.ultramic.2016.12.020
    22 https://doi.org/10.1049/iet-ipr.2013.0330
    23 https://doi.org/10.1080/09500340.2013.787465
    24 https://doi.org/10.1080/13682199.2017.1408254
    25 https://doi.org/10.1103/physrevd.63.123002
    26 https://doi.org/10.1109/have.2005.1545652
    27 https://doi.org/10.1109/icassp.1996.543670
    28 https://doi.org/10.1109/icip.1994.413269
    29 https://doi.org/10.1109/icip.2005.1530011
    30 https://doi.org/10.1109/ipta.2012.6469552
    31 https://doi.org/10.1109/ipta.2015.7367112
    32 https://doi.org/10.1109/lsp.2007.906221
    33 https://doi.org/10.1109/omnvis.2002.1044483
    34 https://doi.org/10.1109/robot.2003.1241653
    35 https://doi.org/10.1109/tip.2003.819861
    36 https://doi.org/10.1109/tsp.2016.2645510
    37 https://doi.org/10.1115/1.4039098
    38 https://doi.org/10.1137/080724265
    39 https://doi.org/10.1137/s1064827596299767
    40 https://doi.org/10.1142/9789812709066_0003
    41 https://doi.org/10.1364/ao.57.006781
    42 https://doi.org/10.3390/s18020408
    43 schema:datePublished 2018-11-09
    44 schema:datePublishedReg 2018-11-09
    45 schema:description This paper discusses the possibility to extend and apply the conventional two dimensional recovering images from blurry and noisy observation with the total variation regularization method to the catadioptric images. The principal in this special method is the stabilization of dual alternating minimization. The latter introduces two auxiliary half quadratic variables to transfer the system out of the ill-posed term. The main contribution of this paper is the use of the inverse stereographic projection and the spherical harmonics in order to adapt this proposed deconvolution with catadioptric omnidirectional images. The projection on the unit sphere of the omnidirectional image, is one way to alleviate the problem of the heterogeneous resolution and the negative effects of anamorphosis. In both anisotropic and isotropic deconvolutions, the experimental results conducted on synthetic as well as captured catadioptric omnidirectional images which are subject to various effects, confirm the performance of the proposed method to restore such images impaired by the blur and noise. Compared with several state-of-the-art approaches, the images resulted can achieve up to an acceptable and higher level of deconvolution quality.
    46 schema:genre research_article
    47 schema:inLanguage en
    48 schema:isAccessibleForFree false
    49 schema:isPartOf sg:journal.1136668
    50 schema:name Reconstruction of catadioptric omnidirectional images using dual alternating total variation minimization
    51 schema:pagination 1-17
    52 schema:productId N648c2aacc541483e9fea6835dfa6f1b3
    53 N64da8e69411a4dceb7a5fe165b36a81e
    54 Ndacefe84424b418aa43ea569d72938d7
    55 schema:sameAs https://app.dimensions.ai/details/publication/pub.1109794221
    56 https://doi.org/10.1007/s12530-018-9257-5
    57 schema:sdDatePublished 2019-04-10T21:56
    58 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    59 schema:sdPublisher N1276a5a6281b47d09209493ffcf3128b
    60 schema:url https://link.springer.com/10.1007%2Fs12530-018-9257-5
    61 sgo:license sg:explorer/license/
    62 sgo:sdDataset articles
    63 rdf:type schema:ScholarlyArticle
    64 N1276a5a6281b47d09209493ffcf3128b schema:name Springer Nature - SN SciGraph project
    65 rdf:type schema:Organization
    66 N648c2aacc541483e9fea6835dfa6f1b3 schema:name readcube_id
    67 schema:value 71384f989bbbefae1dadb82ed16f847e70b8ee51fc951bfdfabb901f2496c821
    68 rdf:type schema:PropertyValue
    69 N64da8e69411a4dceb7a5fe165b36a81e schema:name doi
    70 schema:value 10.1007/s12530-018-9257-5
    71 rdf:type schema:PropertyValue
    72 N97ef742cb2ca42a7a17d87bb5488f060 rdf:first sg:person.013612572172.43
    73 rdf:rest Nc80cf2e0101442ce8a61e7586f8505e7
    74 Nc80cf2e0101442ce8a61e7586f8505e7 rdf:first sg:person.014157217771.40
    75 rdf:rest rdf:nil
    76 Ndacefe84424b418aa43ea569d72938d7 schema:name dimensions_id
    77 schema:value pub.1109794221
    78 rdf:type schema:PropertyValue
    79 Nefbe39ed0c5d48618f1bb7831183a428 rdf:first sg:person.014030375003.86
    80 rdf:rest N97ef742cb2ca42a7a17d87bb5488f060
    81 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
    82 schema:name Information and Computing Sciences
    83 rdf:type schema:DefinedTerm
    84 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
    85 schema:name Artificial Intelligence and Image Processing
    86 rdf:type schema:DefinedTerm
    87 sg:journal.1136668 schema:issn 1868-6478
    88 1868-6486
    89 schema:name Evolving Systems
    90 rdf:type schema:Periodical
    91 sg:person.013612572172.43 schema:affiliation https://www.grid.ac/institutes/grid.442444.6
    92 schema:familyName Boukrouche
    93 schema:givenName Abdelhani
    94 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013612572172.43
    95 rdf:type schema:Person
    96 sg:person.014030375003.86 schema:affiliation https://www.grid.ac/institutes/grid.440473.0
    97 schema:familyName Zenati
    98 schema:givenName Soraya
    99 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014030375003.86
    100 rdf:type schema:Person
    101 sg:person.014157217771.40 schema:affiliation https://www.grid.ac/institutes/grid.15878.33
    102 schema:familyName Boubchir
    103 schema:givenName Larbi
    104 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014157217771.40
    105 rdf:type schema:Person
    106 sg:pub.10.1007/978-3-319-74690-6_14 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100657694
    107 https://doi.org/10.1007/978-3-319-74690-6_14
    108 rdf:type schema:CreativeWork
    109 sg:pub.10.1007/978-981-10-8702-8_1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1103671522
    110 https://doi.org/10.1007/978-981-10-8702-8_1
    111 rdf:type schema:CreativeWork
    112 sg:pub.10.1007/s00041-003-0018-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005843436
    113 https://doi.org/10.1007/s00041-003-0018-9
    114 rdf:type schema:CreativeWork
    115 sg:pub.10.1007/s00138-010-0312-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1030196889
    116 https://doi.org/10.1007/s00138-010-0312-x
    117 rdf:type schema:CreativeWork
    118 sg:pub.10.1007/s00138-011-0368-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052885626
    119 https://doi.org/10.1007/s00138-011-0368-2
    120 rdf:type schema:CreativeWork
    121 sg:pub.10.1007/s00138-012-0424-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044717250
    122 https://doi.org/10.1007/s00138-012-0424-6
    123 rdf:type schema:CreativeWork
    124 sg:pub.10.1007/s00138-012-0426-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051764940
    125 https://doi.org/10.1007/s00138-012-0426-4
    126 rdf:type schema:CreativeWork
    127 sg:pub.10.1007/s00138-012-0451-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031372258
    128 https://doi.org/10.1007/s00138-012-0451-3
    129 rdf:type schema:CreativeWork
    130 sg:pub.10.1007/s00138-014-0624-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017113095
    131 https://doi.org/10.1007/s00138-014-0624-3
    132 rdf:type schema:CreativeWork
    133 sg:pub.10.1007/s002110050258 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030690016
    134 https://doi.org/10.1007/s002110050258
    135 rdf:type schema:CreativeWork
    136 sg:pub.10.1007/s10846-011-9588-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1050678333
    137 https://doi.org/10.1007/s10846-011-9588-y
    138 rdf:type schema:CreativeWork
    139 sg:pub.10.1007/s10851-017-0724-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084027243
    140 https://doi.org/10.1007/s10851-017-0724-6
    141 rdf:type schema:CreativeWork
    142 sg:pub.10.1023/a:1013610201135 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005871774
    143 https://doi.org/10.1023/a:1013610201135
    144 rdf:type schema:CreativeWork
    145 https://doi.org/10.1006/aama.1994.1008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007481173
    146 rdf:type schema:CreativeWork
    147 https://doi.org/10.1016/0167-2789(92)90242-f schema:sameAs https://app.dimensions.ai/details/publication/pub.1030232634
    148 rdf:type schema:CreativeWork
    149 https://doi.org/10.1016/j.ijleo.2013.05.146 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017442585
    150 rdf:type schema:CreativeWork
    151 https://doi.org/10.1016/j.ijleo.2014.01.068 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022792398
    152 rdf:type schema:CreativeWork
    153 https://doi.org/10.1016/j.ultramic.2016.12.020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051571172
    154 rdf:type schema:CreativeWork
    155 https://doi.org/10.1049/iet-ipr.2013.0330 schema:sameAs https://app.dimensions.ai/details/publication/pub.1056829245
    156 rdf:type schema:CreativeWork
    157 https://doi.org/10.1080/09500340.2013.787465 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033860978
    158 rdf:type schema:CreativeWork
    159 https://doi.org/10.1080/13682199.2017.1408254 schema:sameAs https://app.dimensions.ai/details/publication/pub.1099696866
    160 rdf:type schema:CreativeWork
    161 https://doi.org/10.1103/physrevd.63.123002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008827496
    162 rdf:type schema:CreativeWork
    163 https://doi.org/10.1109/have.2005.1545652 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093315520
    164 rdf:type schema:CreativeWork
    165 https://doi.org/10.1109/icassp.1996.543670 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095467643
    166 rdf:type schema:CreativeWork
    167 https://doi.org/10.1109/icip.1994.413269 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094806947
    168 rdf:type schema:CreativeWork
    169 https://doi.org/10.1109/icip.2005.1530011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095703294
    170 rdf:type schema:CreativeWork
    171 https://doi.org/10.1109/ipta.2012.6469552 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093389842
    172 rdf:type schema:CreativeWork
    173 https://doi.org/10.1109/ipta.2015.7367112 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094308854
    174 rdf:type schema:CreativeWork
    175 https://doi.org/10.1109/lsp.2007.906221 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061377065
    176 rdf:type schema:CreativeWork
    177 https://doi.org/10.1109/omnvis.2002.1044483 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094135591
    178 rdf:type schema:CreativeWork
    179 https://doi.org/10.1109/robot.2003.1241653 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095327818
    180 rdf:type schema:CreativeWork
    181 https://doi.org/10.1109/tip.2003.819861 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061640964
    182 rdf:type schema:CreativeWork
    183 https://doi.org/10.1109/tsp.2016.2645510 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061806034
    184 rdf:type schema:CreativeWork
    185 https://doi.org/10.1115/1.4039098 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100649936
    186 rdf:type schema:CreativeWork
    187 https://doi.org/10.1137/080724265 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062854762
    188 rdf:type schema:CreativeWork
    189 https://doi.org/10.1137/s1064827596299767 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062884404
    190 rdf:type schema:CreativeWork
    191 https://doi.org/10.1142/9789812709066_0003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1088727854
    192 rdf:type schema:CreativeWork
    193 https://doi.org/10.1364/ao.57.006781 schema:sameAs https://app.dimensions.ai/details/publication/pub.1106028680
    194 rdf:type schema:CreativeWork
    195 https://doi.org/10.3390/s18020408 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100754350
    196 rdf:type schema:CreativeWork
    197 https://www.grid.ac/institutes/grid.15878.33 schema:alternateName Paris 8 University
    198 schema:name LIASD research Lab., University of Paris 8, 2 rue de la Liberté, 93526, Saint-Denis, France
    199 rdf:type schema:Organization
    200 https://www.grid.ac/institutes/grid.440473.0 schema:alternateName Badji Mokhtar University
    201 schema:name Department of Computer Sciences, Badji Mokhtar University, PO Box 12, 23000, Annaba, Algeria
    202 Laboratory of Inverse Problems, Modelling, Information and Systems, University 8 Mai 1945 Guelma, PO Box 401, 24000, Guelma, Algeria
    203 rdf:type schema:Organization
    204 https://www.grid.ac/institutes/grid.442444.6 schema:alternateName Université 8 mai 1945 Guelma
    205 schema:name Laboratory of Inverse Problems, Modelling, Information and Systems, University 8 Mai 1945 Guelma, PO Box 401, 24000, Guelma, Algeria
    206 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...