A Gamut-Mapping Framework for Color-Accurate Reproduction of HDR Images

Download
2016-07-01
SİKUDOVA, Elena
POULİ, Tania
ARTUSİ, Alessandro
Akyüz, Ahmet Oğuz
BANTERLE, Francesco
Mazlumoglu, Zeynep Miray
REİNHARD, Erik
An integrated gamut- and tone-management framework for color-accurate reproduction of high dynamic range images can prevent hue and luminance shifts while taking gamut boundaries into consideration. The proposed approach is conceptually and computationally simple, parameter-free, and compatible with existing tone-mapping operators.
IEEE COMPUTER GRAPHICS AND APPLICATIONS

Suggestions

An Experimental Method to Determine Quantization Levels for High Luminance Patterns
Sözer, Sevim Begüm; Koz, Alper; Akyüz, Ahmet Oğuz; Zerman, Emin; Valenzise, Giuseppe; Dufaux, Frederic (2020-10-05)
The quantization levels, which forms an important basis for video coding, are mainly determined for 8-bit image representation and for low dynamic range (LDR) typical displays with a luminance level of 100-500 cd/ m 2 . The quantization levels have not been studied until now for high luminance patterns and high dynamic range (HDR) displays, which can reach up to 4000 cd/m 2 . In this study, an HDR display based perceptual experimental method is proposed in order to determine just noticeable quantization lev...
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....
Privacy protection of tone-mapped HDR images using false colours
ÇİFTÇİ, Serdar; Akyüz, Ahmet Oğuz; PİNHEİRO, Antonio M. G.; Ebrahimi, Touradj (2017-12-01)
High dynamic range (HDR) imaging has been developed for improved visual representation by capturing a wide range of luminance values. Owing to its properties, HDR content might lead to a larger privacy intrusion, requiring new methods for privacy protection. Previously, false colours were proved to be effective for assuring privacy protection for low dynamic range (LDR) images. In this work, the reliability of false colours when used for privacy protection of HDR images represented by tone-mapping operators...
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...
Directional coding of backward compatible high dynamic range (HDR) image coding residues
Feyiz, Kutan; Kamışlı, Fatih; Department of Electrical and Electronics Engineering (2018)
High dynamic range (HDR) image and video formats are proposed to overcome limitations of widely accepted standard 8-bit low dynamic range (LDR) image and video representations. The main aim of these formats is to encode the whole luminance range of real world scenes which changes from extreme darkness ( 10 − 6 cd/ m 2 ) to bright sunshine ( 10 8 cd/ m 2 ), and to generate and store such scenes independent from the display technology. To achieve a successful transition from LDR to HDR technology, backward ...
Citation Formats
E. SİKUDOVA et al., “A Gamut-Mapping Framework for Color-Accurate Reproduction of HDR Images,” IEEE COMPUTER GRAPHICS AND APPLICATIONS, pp. 78–90, 2016, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/42934.