KEYWORDS: RGB color model, Cameras, Image quality, Color difference, Nickel, Digital cameras, Visualization, Photography, Matrix multiplication, Facial recognition systems
In these days, most of cellular phones have built-in digital camera. As number of pixels approaches to that of digital still
cameras, consumer's expectation of image quality taken by cellular phone camera is increasing. Automatic white balance
is a function to provide illuminant independent image quality. In this paper, a new automatic white balance method
suitable for cellular phone is proposed. Camera images are divided into three categories. They are first classified as
images with dominant color or images with variety of colors. Images having variety of colors are further divided into two
subclasses based on the existence of highlight area; images with and without highlight regions. Three different AWB
techniques are designed and applied to each of three classes. Experimental results indicate that the proposed technique
yields better performance than the conventional methods.
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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