scholarly journals ZCAM, a colour appearance model based on a high dynamic range uniform colour space

2021 ◽  
Vol 29 (4) ◽  
pp. 6036
Author(s):  
Muhammad Safdar ◽  
Jon Yngve Hardeberg ◽  
Ming Ronnier Luo
Keyword(s):  
Dynamic Range ◽  
High Dynamic Range ◽  
Appearance Model ◽  
Colour Space ◽  
Model Based ◽  
High Dynamic ◽  
Colour Appearance

A Colour Appearance Model based on Jzazbz Colour Space

2018 ◽  
Vol 2018 (1) ◽  
pp. 96-101
Author(s):  
Muhammad Safdar ◽  
Jon Y. Hardeberg ◽  
Youn Jin Kim ◽  
Ming Ronnier Luo
Keyword(s):  
Appearance Model ◽  
Colour Space ◽  
Model Based ◽  
Colour Appearance

A new corresponding color dataset covering a wide luminance range under high dynamic range viewing condition

2021 ◽  
Vol 2021 (29) ◽  
pp. 184-187
Author(s):  
Shi Xinye ◽  
Zhu Yuechen ◽  
Ming Ronnier Luo
Keyword(s):  
Dynamic Range ◽  
High Dynamic Range ◽  
Color Appearance ◽  
Appearance Model ◽  
Viewing Condition ◽  
Color Changes ◽  
Wide Range ◽  
Illuminance Level ◽  
High Dynamic ◽  
The Relationship

An experiment was carried out to investigate the change of color appearance for 13 surface stimuli viewed under a wide range of illuminance levels (15-32000 lux) using asymmetrical matching method. Addition to the above, in the visual field, observers viewed colours in a dark (10 lux) and a bright (200000 lux) illuminance level at the same time to simulate HDR viewing condition. The results were used to understand the relationship between the color changes under HDR conditions, to generate a corresponding color dataset and to verify color appearance model, such as CIECAM16.

Efficient Model-based Tonemapping of High Dynamic Range Gigapixel Images

2013 ◽  
Author(s):  
Esteban Vera ◽  
Dathon Golish ◽  
Qian Gong ◽  
David Kittle ◽  
Steve Feller ◽  
...  
Keyword(s):  
Dynamic Range ◽  
High Dynamic Range ◽  
Model Based ◽  
High Dynamic

TWO-DIMENSIONAL COLOUR APPEARANCE SCALES FOR COLOUR STIMULI HAVING HIGH DYNAMIC RANGE

2021 ◽  
Author(s):  
Lv Xi ◽  
Luo Ming Ronnier
Keyword(s):  
Dynamic Range ◽  
High Dynamic Range ◽  
Quality Enhancement ◽  
Two Dimensional ◽  
Wide Dynamic Range ◽  
Daily Experience ◽  
Image Quality Enhancement ◽  
High Dynamic ◽  
Colour Appearance ◽  
Recent Extension

New colour appearance scales close to daily experience and image quality enhancement are highly desired including whiteness, blackness, vividness and depth. This article describes a new experiment to accumulate the data under HDR (high dynamic range) conditions. The data were then used to test the performance of different colour appearance scales such as CIELAB and CAM16-UCS plus the recent extension by Berns’ Vab*, Dab*. The results showed those Berns’ scales gave reasonable performance. However, there was no scale capable of predicting colour appearance data covering a wide dynamic range. New scales were developed based on the absolute scales of brightness and colourfulness of CAM16-UCS and gave accurate prediction to the data.

New colour appearance scales under high dynamic range conditions

2021 ◽  
Vol 2021 (29) ◽  
pp. 175-178
Author(s):  
Lv Xi ◽  
Ming Ronnier Luo
Keyword(s):  
Image Quality ◽  
Dynamic Range ◽  
High Dynamic Range ◽  
Quality Enhancement ◽  
Wide Dynamic Range ◽  
Daily Experience ◽  
Image Quality Enhancement ◽  
High Dynamic ◽  
Colour Appearance ◽  
Recent Extension

New colour appearance scales close to daily experience and image quality enhancement are highly desired including whiteness, blackness, vividness and depth. This article describes a new experiment to accumulate the data under HDR (high dynamic range) conditions. The data were then used to test the performance of different colour appearance scales such as CIELAB and CAM16-UCS plus the recent extension by Berns' Vab*, Dab*. The results showed those Berns' scales gave a reasonable performance. However, it was found no scale is capable of predicting colour appearance data covering a wide dynamic range. New scales were developed based on the absolute scales of brightness and colourfulness of CAM16-UCS and gave accurate predictions to the data.

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