KEYWORDS: Skin, Databases, Televisions, Visualization, Image quality, Color reproduction, Fluctuations and noise, Image classification, RGB color model, Data communications
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
extraction.
KEYWORDS: Skin, Visualization, Image quality, Televisions, Target detection, LCDs, Color difference, Digital image processing, RGB color model, Color reproduction
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.
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