2016
Journal article  Open Access

Mixing tone mapping operators on the GPU by differential zone mapping based on psychophysical experiments

Banterle F., Artusi A., Sikudova E., Ledda P., Bashford-Rogers T., Chalmers A., Bloj M.

Electrical and Electronic Engineering  Video Tone Mapping  High Dynamic Range Imaging  Computer Vision and Pattern Recognition  Software  Tone Mapping  GPU  Signal Processing 

In this paper, we present a new technique for displaying High Dynamic Range (HDR) images on Low Dynamic Range (LDR) displays in an efficient way on the GPU. The described process has three stages. First, the input image is segmented into luminance zones. Second, the tone mapping operator (TMO) that performs better in each zone is automatically selected. Finally, the resulting tone mapping (TM) outputs for each zone are merged, generating the final LDR output image. To establish the TMO that performs better in each luminance zone we conducted a preliminary psychophysical experiment using a set of HDR images and six different TMOs. We validated our composite technique on several (new) HDR images and conducted a further psychophysical experiment, using an HDR display as the reference that establishes the advantages of our hybrid three-stage approach over a traditional individual TMO. Finally, we present a GPU version, which is perceptually equal to the standard version but with much improved computational performance.

Source: Signal processing. Image communication 48 (2016): 50–62. doi:10.1016/j.image.2016.09.004

Publisher: Elsevier, Oxford ;, Paesi Bassi


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BibTeX entry
@article{oai:it.cnr:prodotti:364861,
	title = {Mixing tone mapping operators on the GPU by differential zone mapping based on psychophysical experiments},
	author = {Banterle F. and Artusi A. and Sikudova E. and Ledda P. and Bashford-Rogers T. and Chalmers A. and Bloj M.},
	publisher = {Elsevier, Oxford ;, Paesi Bassi},
	doi = {10.1016/j.image.2016.09.004},
	journal = {Signal processing. Image communication},
	volume = {48},
	pages = {50–62},
	year = {2016}
}