An evaluation of image reproduction algorithms for high contrast scenes on large and small screen display devices

Date

2013-11-01

Author

Akyüz, Ahmet Oğuz
Aydın, Murat

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

220
views

0
downloads

Rendering high contrast scenes on display devices with limited dynamic range is a challenging task. Two groups of algorithms have emerged to take up this challenge: tone mapping operators (TMOs) and more recently exposure fusion (EF) techniques. While several formal evaluation studies comparing TMOs exist, no formal evaluation has yet been performed that compares EF techniques with each other or compares them against TMOs. Moreover, with the advancements in hand-held devices and programmable digital cameras it became possible to directly capture and view high dynamic range (HDR) content on these devices which are characterized by their small screens. However, currently very little is known about how to best visualize a high contrast scene on a small screen. Thus the primary goal of this paper is to provide answers to both of these questions by conducting a series of rigorous psychophysical experiments. Our results suggest that the best tone mapping algorithms are generally superior to EF algorithms except for the reproduction of colors. Furthermore, contrary to some previous work, we find that the differences between algorithms are barely perceptible on small screens and therefore one can opt for a simpler solution than a more complex and accurate one.

Subject Keywords

HDR imaging, Tone mapping, Exposure fusion

URI

https://hdl.handle.net/11511/35582

Journal

COMPUTERS & GRAPHICS-UK

DOI

https://doi.org/10.1016/j.cag.2013.07.004

Collections

Department of Computer Engineering, Article

Suggestions

OpenMETU
Core

Evaluation of tone mapping and exposure fusion algorithms on HDR videos for face detection and recognition Çavdarlı, Fehime Betül; Akyüz, Ahmet Oğuz; Department of Computer Engineering (2022-2-08) High dynamic range (HDR) images have become popular recently especially for video surveillance systems. One of the most important reasons for this is that in areas where there is under or over-exposure, classical low dynamic range (LDR) images are insufficient to capture details, while HDR images have better visual details and contain wide range illumination values. However, since HDR images cannot be viewed on conventional LDR displays, additional processing such as tonemapping and/or fusion are required t...
Visual similarity for hdr images with applications to tone mapping Aydınlılar, Merve; Akyüz, Ahmet Oğuz; Tarı, Zehra Sibel; Department of Computer Engineering (2021-2-15) Assessing visual similarity between images is important for many computer vision applications. So far, investigations on visual similarity have been confined to low dynamic range images. However, recently, there is a growing interest to high dynamic range (HDR) imaging. In this thesis, the aim is to shed light on visual image similarity for HDR images by following an experimental approach. To this end, a user experiment is conducted through a novel web-based interface, in which the participants assess the p...
Automatic saturation correction for dynamic range management algorithms Artusi, Alessandro; POULİ, Tania; BANTERLE, Francesco; Akyüz, Ahmet Oğuz (2018-04-01) High dynamic range (HDR) images require tone reproduction to match the range of values to the capabilities of a display. For computational reasons and given the absence of fully calibrated imagery, rudimentary color reproduction is often added as a post-processing step rather than integrated into tone reproduction algorithms. In the general case, this currently requires manual parameter tuning, and can be automated only for some global tone reproduction operators by inferring parameters from the tone curve....
An Investigation on hyperspectral image classifiers for remote sensing Özdemir, Okan Bilge; Çetin, Yasemin; Department of Information Systems (2013) Hyperspectral image processing is improved by the capabilities of multispectral image processing with high spectral resolution. In this thesis, we explored hyperspectral classification with Support Vector Machines (SVM), Maximum Likelihood (ML) and KNearest Neighborhood algorithms. We analyzed the effect of training data on classification accuracy. For this purpose, we implemented three different training data selection methods; first N sample selection, randomly N sample selection and uniformly N sample se...
An Evaluation of ghost removal algorithms for exposure fusion Kutlu, Tuğser; Akar, Gözde; Department of Electrical and Electronics Engineering (2015) In high dynamic range imaging (HDR), the goal is to capture a scene with a higher dynamic range than the camera capable of capturing with a single exposure. Similar to HDR, exposure fusion is a process that takes multiple images and combines them to create a single dynamically enhanced image by only keeping the properly exposed elements. When using multiple images, local motion of objects can influence the quality of the final image in such a way that local motion of objects causes a ghost artifact. In this...

Citation Formats

A. O. Akyüz and M. Aydın, “An evaluation of image reproduction algorithms for high contrast scenes on large and small screen display devices,” COMPUTERS & GRAPHICS-UK, pp. 885–895, 2013, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/35582.