Improving color reproduction accuracy of a mobile liquid crystal display

Abstract

The default method for color representation on displays involves sRGB as device-independent encoding color space. For improving color reproduction accuracy, we develop a device-specific display characterization model for the Apple iPad Air 2. In separate articles, we will evaluate the same method for other devices and for other display technologies. This model is combined with an easy-to-implement new method to account for the influence of illuminance from ambient light. The combination is called the mobile display characterization and illumination model (MDCIM) for the iPad Air 2, representing modern liquid crystal displays. Seven observers performed psychophysical tests at ambient illuminance levels from 600 to 3000 lx. They visually compared colors of calculated images with those of physical samples. The MDCIM model achieves similar color reproduction accuracy as when using the default method involving sRGB encoding at 1000 lx, while considerably improving color accuracy at other illuminance levels. At 600 lx, 98% of the observers prefer images directly generated with the MDCIM model over those created using the default method. The average color reproduction accuracy improves by two categories on a five-point scale. At 3000 lx, the percentage of colors that is represented at least reasonably well, according to the subjective assessment of visual observers, increased from 0% to 60%.

Digitally reconstructing Van Gogh'sField with Irises near Arlespart 3: Determining the original colors

“…Apart from that, improved color representation is also expected when the digital representation is calculated specifically for the type of display. For the display of the iPad Air 2, such device‐dependent calculations have recently been published …”

“…For the display of the iPad Air 2, such device-dependent calculations have recently been published. 32 For discussing the color accuracy of the digital reconstruction, we have calculated a reference image as shown in Figure 11. This image was calculated by following the same procedure as was used for calculating the main reconstruction ( Figure 9B) as far as the pigments chrome yellow, eosin, and cochineal are concerned.…”

A multi‐primary empirical model based on a quantum dots display technology

“…We worked with a commercialized Philips Brilliance LCD monitor (MultiView 272P4QPJKES Quad HD 27″/68.6 cm 2560 × 1440) display. The standard color display calibration method “gain‐offset‐gamma” (GOG) was used mainly for CRT displays, although using visual science and experiments is also commonplace . The GOG model provided the existent relation between the channel signal of the display and the luminance ( L ) generated by this channel (electro‐optical transfer function; EOTF) through Equation : …”

“…A narrow 5‐unit interval was chosen to completely cover low levels [0‐50], while a wider 25‐unit interval was selected to cover the rest of the range [50‐255]. The selection of a narrow interval at low levels was due to minor radiance changes, which allow this problematic area to be better represented . Two additional stimuli were generated to simulate the white stimulus ( R = G = B = max) and the dark stimulus ( R = G = B = 0).…”

“…The selection of a narrow interval at low levels was due to minor radiance changes, which allow this problematic area to be better represented. 15,16 Two additional stimuli were generated to simulate the white stimulus (R = G = B = max) and the dark stimulus (R = G = B = 0). Luminance and spectral measurements were taken using the tele-spectroradiometer Konica Minolta CS2000.…”