Template based Inter-Layer Prediction for High Dynamic Range Scalable compression

Mikael Le Pendu 1, 2 Christine Guillemot 2 Dominique Thoreau 1
2 Sirocco - Analysis representation, compression and communication of visual data
Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
Abstract : This paper presents a scalable high dynamic range (HDR) image coding framework in which the base layer is a low dynamic range (LDR) version of the image that may have been generated by an arbitrary Tone Mapping Operator (TMO). Our method successfully handles the case of complex local TMOs thanks to a block-wise and non-linear approach. A novel template based Inter Layer Prediction (ILP) is designed in order to perform the inverse tone mapping of a block without the need to transmit any additional parameter to the decoder. This method enables the use of a more accurate inverse tone mapping model than the simple linear regression commonly used for block-wise ILP. Our experiments have shown an average bitrate saving of 34% on the HDR enhancement layer, compared to state of the art methods.
Type de document :
Communication dans un congrès
IEEE International Conference on Image Processing (ICIP), Sep 2015, Quebec, Canada. proceedings, 2015
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https://hal.inria.fr/hal-01204715
Contributeur : Mikael Le Pendu <>
Soumis le : jeudi 24 septembre 2015 - 14:45:28
Dernière modification le : mardi 16 janvier 2018 - 15:54:20

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  • HAL Id : hal-01204715, version 1

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Mikael Le Pendu, Christine Guillemot, Dominique Thoreau. Template based Inter-Layer Prediction for High Dynamic Range Scalable compression. IEEE International Conference on Image Processing (ICIP), Sep 2015, Quebec, Canada. proceedings, 2015. 〈hal-01204715〉

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