Many display manufacturers have studied RGBW pixel structure adding a white sub-pixel to RGB LCD and recently
revealed UHD TVs based on novel RGBW LCD. The RGBW LCD has 50% higher white luminance and 25% lower
primary color luminance compared to RGB LCD.
In this paper, the image quality of RGBW and RGB LCD was dealt with. Before evaluating them, TV broadcast video
and IEC-62087 video were analyzed for test video clips. In order to analyze them, a TV reference video from TV
broadcast content in Korea was firstly collected. As a result of TV reference video analysis, RGBW LCD was expected
to improve image quality more because most of colors are distributed around white point and population ratio of
achromatic colors is higher.
RGB, RGBW and RGBW using wide color gamut (WCG) backlight unit (BLU) LCDs were prepared, and a series of
visual assessments were conducted. As a result, RGBW LCD obtained higher scores than RGB LCD about four
attributes (‘Brightness’, ‘Naturalness’, ‘Contrast’ and overall image quality) and ‘Colorfulness’ was not higher score
than RGB LCD in test still images. RGBW LCD’s overall image quality in the TV reference video clips also was
assessed higher than RGB LCD. Additionally, RGBW LCD using WCG BLU shows better performance about
especially ‘Colorfulness’ than RGBW LCD.
Instead of colorimetirc color reproduction, preferred color correction is applied for digital TVs to improve subjective
image quality. First step of the preferred color correction is to survey the preferred color coordinates of memory colors.
This can be achieved by the off-line human visual tests. Next step is to extract pixels of memory colors representing skin,
grass and sky. For the detected pixels, colors are shifted towards the desired coordinates identified in advance. This
correction process may result in undesirable contours on the boundaries between the corrected and un-corrected areas.
For digital TV applications, the process of extraction and correction should be applied in every frame of the moving
images. This paper presents a preferred color correction method in LCH color space. Values of chroma and hue are
corrected independently. Undesirable contours on the boundaries of correction are minimized. The proposed method
change the coordinates of memory color pixels towards the target color coordinates. Amount of correction is determined
based on the averaged coordinate of the extracted pixels. The proposed method maintains the relative color difference
within memory color areas. Performance of the proposed method is evaluated using the paired comparison. Results of
experiments indicate that the proposed method can reproduce perceptually pleasing images to viewers.
Subjective image quality is one of the most important performance indicators for digital TVs. In order to improve
subjective image quality, preferred color correction is often employed. More specifically, areas of memory colors such as
skin, grass, and sky are modified to generate pleasing impression to viewers. Before applying the preferred color
correction, tendency of preference for memory colors should be identified. It is often accomplished by off-line human
visual tests. Areas containing the memory colors should be extracted then color correction is applied to the extracted
areas. These processes should be performed on-line. This paper presents a new method for area extraction of three types
of memory colors. Performance of the proposed method is evaluated by calculating the correct and false detection ratios.
Experimental results indicate that proposed method outperform previous methods proposed for the memory color
This paper proposes a color decomposition method for a multi-primary display (MPD) using a 3-dimensional look-up-table (3D-LUT) in linearized LAB space. The proposed method decomposes the conventional three primary colors into multi-primary control values for a display device under the constraints of tristimulus matching. To reproduce images on an MPD, the color signals are estimated from a device-independent color space, such as CIEXYZ and CIELAB. In this paper, linearized LAB space is used due to its linearity and additivity in color conversion. First, the proposed method constructs a 3-D LUT containing gamut boundary information to calculate the color signals for the MPD in linearized LAB space. For the image reproduction, standard RGB or CIEXYZ is transformed to linearized LAB, then the hue and chroma are computed with reference to the 3D-LUT. In linearized LAB space, the color signals for a gamut boundary point are calculated to have the same lightness and hue as the input point. Also, the color signals for a point on the gray axis are calculated to have the same lightness as the input point. Based on the gamut boundary points and input point, the color signals for the input point are then obtained using the chroma ratio divided by the chroma of the gamut boundary point. In particular, for a change of hue, the neighboring boundary points are also employed. As a result, the proposed method guarantees color signal continuity and computational efficiency, and requires less memory.