We investigated the effects of color coordinate systems on the processing of
digital color images.
This work involved several subprojects: luminance quantization error
in histogram modification, techniques for bypassing color coordinate
transformations, and saturation clipping in histogram modification.
Luminance quantization error in histogram modification
For color images, histogram modification is usually applied to the quantized
luminance component.
However, the luminance quantization error can be significantly magnified by
the transformation function, leading to distortion in the processed image.
The propagation of the quantization error was analyzed theoretically to
determine the worst-case error.
The relationship between the number of luminance quantization levels and the
output quantization error was derived.
Experimental results with histogram equalization demonstrated that
the use of a higher-resolution histogram leads to reduced distortion as well as
a "flatter" output histogram.
Efficient techniques for bypassing color coordinate transformations
In many applications of color image processing, only modification of the
luminance component is desired. However, the commonly used coordinate systems,
such as HSI, LHS, and YIQ, are not perceptually orthogonal; that is, luminance
modification can cause perceptual shifts in the hue and saturation.
We performed a theoretical analysis of this phenomenon. Efficient
techniques were developed for bypassing the costly coordinate transformations
when only the luminance or only the saturation is to be modified. Experimental
results using histogram equalization supported the theoretical analysis.
Saturation clipping in histogram modification
In histogram modification of the luminance component of color images,
the gamut limitation of the color coordinate system is an important issue.
The processed luminance value of a pixel can fall outside the gamut of the
color space.
Traditionally, in such cases the luminance is clipped to keep the color
vector within the gamut.
But this procedure can reduce the effective contrast in the image.
Instead, we have proposed clipping the saturation of the color vector.
For most images, the change in saturation is not so perceptible
as the change in luminance.
Experimental results demonstrated that improved contrast was achieved
by this approach.
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