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I3D: a new dataset for testing denoising and demosaicing algorithms

Abstract

In this paper we present a dataset of images to test the performance of image processing algorithms, in particular demosaicing and denoising methods. Despite the plethora of demosaicing and denoising algorithms present in the literature, only few benchmarks are available to test their performance, and most of them are quite old, thus inadequate to represent the images captured by modern devices. The proposed dataset is composed by twenty 16 bit-depth images that can be used to test full-reference image quality metrics. More specifically, twelve pictures have been synthetically created by means of 2D or 3D softwares, while eight images have been captured by a high-end digital camera.

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Notes

  1. 1.

    To check the dark bias, a picture with a 1/8000 sec of exposure time, and the cap in front of the lens was taken. For the white point, we took a picture of a light source, in particular a lamp big enough to cover almost all the viewing area, for 15 sec, to be sure to saturate the sensor.

  2. 2.

    These operations are needed to take account of the two pedestals, and to transform the linear raw values in sRGB.

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Acknowledgments

We would like to thank John McCann, Prof. Bradley Lucier and Prof. Michael Kriss, that answered to our questions about the Kodak Photo CD.

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Correspondence to Cristian Bonanomi.

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This work was partially supported by the “Ministero degli Affari Esteri e della Cooperazione Internazionale” of Italy under Grant PGR00217.

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Bonanomi, C., Balletti, S., Lecca, M. et al. I3D: a new dataset for testing denoising and demosaicing algorithms. Multimed Tools Appl 79, 8599–8626 (2020). https://doi.org/10.1007/s11042-018-6396-4

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Keywords

  • Image dataset
  • Demosaicing
  • Denoising
  • Image quality