@InProceedings{7760577,
  author = {B. C. Thai and A. Mokraoui and B. Matei},
  booktitle = {2016 24th European Signal Processing Conference (EUSIPCO)},
  title = {Performance evaluation of high dynamic range image tone mapping operators based on separable non-linear multiresolution families},
  year = {2016},
  pages = {1891-1895},
  abstract = {This paper addresses the conversion problem of High Dynamic Range (HDR) images into Low Dynamic Range (LDR) images. In this objective, separable non-linear multiresolution approaches are exploited as Image Tone Mapping Operators (TMOs). They are related on: (i) Essentially Non-Oscillatory (ENO) interpolation strategy developed by Harten namely Point-Value (PV) multiresolution family and Cell-Average (CA) multiresolution family; and (ii) Power-P multiresolution family introduced by Amat. These approaches have the advantage to take into account the singularities, such as edge points of the image, in the mathematical model thus preserving the structural information of the HDR images. Moreover the Gibbs phenomenon, harmful in tone mapped images, is avoided. The quality assessment of the tone mapped images is measured according to the TMQI metric. Simulation results show that the proposed TMOs provide good results compared to traditional TMO strategies.},
  keywords = {image resolution;interpolation;high dynamic range image tone mapping operator performance evaluation;separable nonlinear multiresolution families;HDR image conversion problem;low dynamic range image;LDR image;image TMO;essentially nonoscillatory interpolation strategy;ENO interpolation strategy;point-value multiresolution family;cell-average multiresolution family;Power-P multiresolution family;mathematical model;Gibbs phenomenon;TMQI metric;Image resolution;Signal resolution;Interpolation;Dynamic range;Image edge detection;Mathematical model;High dynamic range;Tone mapping;Essentially non-oscillatory interpolation;Non-linear multiresolution;Point-value and cell-average multiresolution;Power-P multiresolution},
  doi = {10.1109/EUSIPCO.2016.7760577},
  issn = {2076-1465},
  month = {Aug},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2016/papers/1570252305.pdf},
}

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In this objective, separable non-linear multiresolution approaches are exploited as Image Tone Mapping Operators (TMOs). They are related on: (i) Essentially Non-Oscillatory (ENO) interpolation strategy developed by Harten namely Point-Value (PV) multiresolution family and Cell-Average (CA) multiresolution family; and (ii) Power-P multiresolution family introduced by Amat. These approaches have the advantage to take into account the singularities, such as edge points of the image, in the mathematical model thus preserving the structural information of the HDR images. Moreover the Gibbs phenomenon, harmful in tone mapped images, is avoided. The quality assessment of the tone mapped images is measured according to the TMQI metric. 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C. Thai and A. Mokraoui and B. Matei},\n booktitle = {2016 24th European Signal Processing Conference (EUSIPCO)},\n title = {Performance evaluation of high dynamic range image tone mapping operators based on separable non-linear multiresolution families},\n year = {2016},\n pages = {1891-1895},\n abstract = {This paper addresses the conversion problem of High Dynamic Range (HDR) images into Low Dynamic Range (LDR) images. In this objective, separable non-linear multiresolution approaches are exploited as Image Tone Mapping Operators (TMOs). They are related on: (i) Essentially Non-Oscillatory (ENO) interpolation strategy developed by Harten namely Point-Value (PV) multiresolution family and Cell-Average (CA) multiresolution family; and (ii) Power-P multiresolution family introduced by Amat. These approaches have the advantage to take into account the singularities, such as edge points of the image, in the mathematical model thus preserving the structural information of the HDR images. Moreover the Gibbs phenomenon, harmful in tone mapped images, is avoided. The quality assessment of the tone mapped images is measured according to the TMQI metric. 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