IEEE Transactions on Image Processing, accepted for publication.

Large-scale Crowdsourced Study for Tone Mapped HDR Pictures

Debarati Kundu (1), Deepti Ghadiyaram (2), Alan C. Bovik (2) and Brian L. Evans (1)

(1) Embedded Signal Processing Laboratory, Wireless Networking and Communications Group, The University of Texas at Austin, Austin, TX 78712 USA
debarati@utexas.edu - bevans@ece.utexas.edu

(2) Laboratory for Image and Video Engineering, Wireless Networking and Communications Group, The University of Texas at Austin, Austin, TX 78712 USA
deepti@cs.utexas.edu - bovik@ece.utexas.edu

Paper Draft

Related Resources: ESPL-LIVE HDR Image Database - No Reference HDR IQA Methods - PhD Dissertation on HDR IQA

Abstract

Measuring digital picture quality, as perceived by human observers, is increasingly important in many applications in which humans are the ultimate consumers of visual information. Standard dynamic range (SDR) images provide 8 bits/color/pixel. High dynamic range (HDR) images, usually created from multiple exposures of the same scene, can provide 16 or 32 bits/color/pixel, but need to be tonemapped to SDR for display on standard monitors. Multi-exposure fusion (MEF) techniques bypass HDR creation by fusing on exposure stack directly to SDR images to achieve aesthetically pleasing luminance and color distributions. Many HDR and MEF databases have a relatively small number of images and human opinion scores, obtained under stringently controlled conditions, thereby limiting realistic viewing. Moreover, many of these databases are intended to compare tone-mapping algorithms, rather than being specialized for developing and comparing IQA models. To overcome these challenges, we conducted a massively crowdsourced online subjective study. The primary contributions described in this paper are
  1. the new ESPL-LIVE HDR Image Database that we created containing diverse images obtained by tone-mapping operators (TMO) and MEF algorithms, with and without post processing;
  2. a large-scale subjective study that we conducted using a crowdsourced platform to gather more than 300,000 opinion scores on 1,811 images from over 5,000 unique observers; and
  3. a detailed study of the correlation performance of state-of-the-art no-reference image quality assessment algorithms against human opinion scores of these images.
The database is available at: http://signal.ece.utexas.edu/~debarati/ESPL_LIVE_HDR_Database/index.html.


Note: IQA means Image Quality Assessment.

The paper mentions five "gold standard" images in the HDR image database, but does not give their names. They are H_Exploratorium_2_surreal.PNG, H_Jesse_Browns_Cabin_FattalTMO.PNG, H_tol_tree_9_grunge2.PNG, H_Waffle_House_RamanTMO.PNG, and H_Hoover_Garage_surreal.PNG.


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Last Updated 05/29/17.