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Sira Ferradans, Marcelo Bertalmio, Edoardo Provenzi, and Vincent Caselles, A multi-modal approach to perceptual tone mapping. JVRB - Journal of Virtual Reality and Broadcasting, 9(2012), no. 7. (urn:nbn:de:0009-6-35145)

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%0 Journal Article
%T A multi-modal approach to perceptual tone mapping
%A Ferradans, Sira
%A Bertalmio, Marcelo
%A Provenzi, Edoardo
%A Caselles, Vincent
%J JVRB - Journal of Virtual Reality and Broadcasting
%D 2013
%V 9(2012)
%N 7
%@ 1860-2037
%F ferradans2013
%X We present an improvement of TSTM, a recently proposed tone mapping operator for High Dynamic Range (HDR) images, based on a multi-modal analysis. One of the key features of TSTM is a suitable implementation of the Naka-Rushton equation that mimics the visual adaptation performed by the human visual system coherently with Weber-Fechner's law of contrast perception. In the present paper we use the Gaussian Mixture Model (GMM) in order to detect the modes of the log-scale luminance histogram of a given HDR image and then we use the information provided by GMM to properly devise a Naka-Rushton equation for each mode. Finally, we properly select the parameters in order to merge those equations into a continuous function. Tests and comparisons to show how this new method is capable of improving the performances of TSTM are provided and commented, as well as comparisons with state of the art methods.
%L 004
%K Gaussian Mixture Model
%K High Dynamic Range Images
%K Naka Rushton Formula
%K Tone Mapping
%K Weber-Fechner Contrast
%R 10.20385/1860-2037/9.2012.7
%U http://nbn-resolving.de/urn:nbn:de:0009-6-35145
%U http://dx.doi.org/10.20385/1860-2037/9.2012.7

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Bibtex

@Article{ferradans2013,
  author = 	"Ferradans, Sira
		and Bertalmio, Marcelo
		and Provenzi, Edoardo
		and Caselles, Vincent",
  title = 	"A multi-modal approach to perceptual tone mapping",
  journal = 	"JVRB - Journal of Virtual Reality and Broadcasting",
  year = 	"2013",
  volume = 	"9(2012)",
  number = 	"7",
  keywords = 	"Gaussian Mixture Model; High Dynamic Range Images; Naka Rushton Formula; Tone Mapping; Weber-Fechner Contrast",
  abstract = 	"We present an improvement of TSTM, a recently proposed tone mapping operator for High Dynamic Range (HDR) images, based on a multi-modal analysis. One of the key features of TSTM is a suitable implementation of the Naka-Rushton equation that mimics the visual adaptation performed by the human visual system coherently with Weber-Fechner's law of contrast perception. In the present paper we use the Gaussian Mixture Model (GMM) in order to detect the modes of the log-scale luminance histogram of a given HDR image and then we use the information provided by GMM to properly devise a Naka-Rushton equation for each mode. Finally, we properly select the parameters in order to merge those equations into a continuous function. Tests and comparisons to show how this new method is capable of improving the performances of TSTM are provided and commented, as well as comparisons with state of the art methods.",
  issn = 	"1860-2037",
  doi = 	"10.20385/1860-2037/9.2012.7",
  url = 	"http://nbn-resolving.de/urn:nbn:de:0009-6-35145"
}

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RIS

TY  - JOUR
AU  - Ferradans, Sira
AU  - Bertalmio, Marcelo
AU  - Provenzi, Edoardo
AU  - Caselles, Vincent
PY  - 2013
DA  - 2013//
TI  - A multi-modal approach to perceptual tone mapping
JO  - JVRB - Journal of Virtual Reality and Broadcasting
VL  - 9(2012)
IS  - 7
KW  - Gaussian Mixture Model
KW  - High Dynamic Range Images
KW  - Naka Rushton Formula
KW  - Tone Mapping
KW  - Weber-Fechner Contrast
AB  - We present an improvement of TSTM, a recently proposed tone mapping operator for High Dynamic Range (HDR) images, based on a multi-modal analysis. One of the key features of TSTM is a suitable implementation of the Naka-Rushton equation that mimics the visual adaptation performed by the human visual system coherently with Weber-Fechner's law of contrast perception. In the present paper we use the Gaussian Mixture Model (GMM) in order to detect the modes of the log-scale luminance histogram of a given HDR image and then we use the information provided by GMM to properly devise a Naka-Rushton equation for each mode. Finally, we properly select the parameters in order to merge those equations into a continuous function. Tests and comparisons to show how this new method is capable of improving the performances of TSTM are provided and commented, as well as comparisons with state of the art methods.
SN  - 1860-2037
UR  - http://nbn-resolving.de/urn:nbn:de:0009-6-35145
DO  - 10.20385/1860-2037/9.2012.7
ID  - ferradans2013
ER  - 
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Wordbib

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<b:Comments>We present an improvement of TSTM, a recently proposed tone mapping operator for High Dynamic Range (HDR) images, based on a multi-modal analysis. One of the key features of TSTM is a suitable implementation of the Naka-Rushton equation that mimics the visual adaptation performed by the human visual system coherently with Weber-Fechner&apos;s law of contrast perception. In the present paper we use the Gaussian Mixture Model (GMM) in order to detect the modes of the log-scale luminance histogram of a given HDR image and then we use the information provided by GMM to properly devise a Naka-Rushton equation for each mode. Finally, we properly select the parameters in order to merge those equations into a continuous function. Tests and comparisons to show how this new method is capable of improving the performances of TSTM are provided and commented, as well as comparisons with state of the art methods.</b:Comments>
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ISI

PT Journal
AU Ferradans, S
   Bertalmio, M
   Provenzi, E
   Caselles, V
TI A multi-modal approach to perceptual tone mapping
SO JVRB - Journal of Virtual Reality and Broadcasting
PY 2013
VL 9(2012)
IS 7
DI 10.20385/1860-2037/9.2012.7
DE Gaussian Mixture Model; High Dynamic Range Images; Naka Rushton Formula; Tone Mapping; Weber-Fechner Contrast
AB We present an improvement of TSTM, a recently proposed tone mapping operator for High Dynamic Range (HDR) images, based on a multi-modal analysis. One of the key features of TSTM is a suitable implementation of the Naka-Rushton equation that mimics the visual adaptation performed by the human visual system coherently with Weber-Fechner's law of contrast perception. In the present paper we use the Gaussian Mixture Model (GMM) in order to detect the modes of the log-scale luminance histogram of a given HDR image and then we use the information provided by GMM to properly devise a Naka-Rushton equation for each mode. Finally, we properly select the parameters in order to merge those equations into a continuous function. Tests and comparisons to show how this new method is capable of improving the performances of TSTM are provided and commented, as well as comparisons with state of the art methods.
ER

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Mods

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  <titleInfo>
    <title>A multi-modal approach to perceptual tone mapping</title>
  </titleInfo>
  <name type="personal">
    <namePart type="family">Ferradans</namePart>
    <namePart type="given">Sira</namePart>
  </name>
  <name type="personal">
    <namePart type="family">Bertalmio</namePart>
    <namePart type="given">Marcelo</namePart>
  </name>
  <name type="personal">
    <namePart type="family">Provenzi</namePart>
    <namePart type="given">Edoardo</namePart>
  </name>
  <name type="personal">
    <namePart type="family">Caselles</namePart>
    <namePart type="given">Vincent</namePart>
  </name>
  <abstract>We present an improvement of TSTM, a recently proposed tone mapping operator for High Dynamic Range (HDR) images, based on a multi-modal analysis. One of the key features of TSTM is a suitable implementation of the Naka-Rushton equation that mimics the visual adaptation performed by the human visual system coherently with Weber-Fechner's law of contrast perception. In the present paper we use the Gaussian Mixture Model (GMM) in order to detect the modes of the log-scale luminance histogram of a given HDR image and then we use the information provided by GMM to properly devise a Naka-Rushton equation for each mode. Finally, we properly select the parameters in order to merge those equations into a continuous function. Tests and comparisons to show how this new method is capable of improving the performances of TSTM are provided and commented, as well as comparisons with state of the art methods.</abstract>
  <subject>
    <topic>Gaussian Mixture Model</topic>
    <topic>High Dynamic Range Images</topic>
    <topic>Naka Rushton Formula</topic>
    <topic>Tone Mapping</topic>
    <topic>Weber-Fechner Contrast</topic>
  </subject>
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        <number>9(2012)</number>
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      <detail type="issue">
        <number>7</number>
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      <date>2013</date>
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  <identifier type="citekey">ferradans2013</identifier>
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