29-10-2012, 01:40 PM
Hue-Preserving Color Image Enhancement Without Gamut Problem
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Abstract
The first step in many techniques for processing intensity
and saturation in color images keeping hue unaltered is the
transformation of the image data from RGB space to other color
spaces such as LHS, HSI, YIQ, HSV, etc. Transforming from one
space to another and processing in these spaces usually generate
gamut problem, i.e., the values of the variables may not be in their
respective intervals. Enhancement techniques for color images are
studied here theoretically in a generalized setup. A principle is suggested
to make the transformations’ gamut problem free in this regard.
Using the same principle a class of hue preserving contrast
enhancement transformations are proposed, which generalize the
existing grey scale contrast intensification techniques to color images.
These transformations are also seen to bypass the above mentioned
color coordinate transformations for image enhancement.
The developed principle is used to generalize the histogram equalization
scheme for grey scale images to color images.
INTRODUCTION
IMAGE enhancement is used to improve the quality of an
image for visual perception of human beings. It is also used
for low level vision applications. It is a task in which the set
of pixel values of one image is transformed to a new set of
pixel values so that the new image formed is visually pleasing
and is also more suitable for analysis. The main techniques
for image enhancement such as contrast stretching, slicing,
histogram equalization, for grey scale images are discussed in
many books. The generalization of these techniques to color
images is not straight forward. Unlike grey scale images, there
are some factors in color images like hue which need to be
properly taken care of for enhancement. These are going to be
discussed here.
Hue, saturation and intensity are the attributes of color [1].
Hue is that attribute of a color which decides what kind of color
it is, i.e., a red or an orange. In the spectrum each color is at the
maximum purity (or strength or richness) that the eye can appreciate,
and the spectrum of colors is described as fully saturated.
If a saturated color is diluted by being mixed with other colors
or with white light, its richness or saturation is decreased [2].
For the purpose of enhancing a color image, it is to be seen that
hue should not change for any pixel. If hue is changed then the
color gets changed, thereby distorting the image.
NON-LINEAR TRANSFORMATIONS
In this section we try to generalize the usual grey scale contrast
enhancement techniques to color images in such a way that
they are hue preserving. The objective is to keep the transformed
values within the range of the RGB space, i.e., the transformations
are free from gamut problem. Some general and widely
used contrast enhancement techniques for grey scale images are
S-type enhancement, piecewise linear stretching, clipping etc.
The methodologies of these techniques can be found in the literature.
Only S-type transformation is listed below for grey scale
images.
Histogram Equalization
Histogram equalization is a very powerful scheme for contrast
enhancement in grey scale images. In grey scale histogram
equalization, the method rearranges the grey values in such a
way that the modified histogram resembles the histogram of uniform
distribution. Intuitively, the same technique should work
on a color image also, i.e., by equalizing the image in three dimensional
space where the three dimensions are the three primary
components of the color space. But this causes unequal
shift in the three components resulting in change of hue of the
pixel [9]. A solution is to equalize only the luminance/saturation
or both the components in the color spaces such as LHS,
HSI, or YIQ. This sometimes leads to gamut problem when the
processed data is again transformed back to RGB space.
CONCLUSION AND DISCUSSION
The main contribution here is the scheme to generalize
any grey scale image enhancement method to color images
without encountering gamut problem. The overall enhancement
obtained by the proposed scheme is mainly dependent on the
already existing different contrast enhancement functions for
grey scale images. These contrast enhancement functions for
grey scale images are generalized to enhance the intensity of
the color images, keeping the hue intact. A novel scheme is
proposed to avoid gamut problem arising during the process of
enhancement. This scheme is used to enhance the intensity of
color images using a general hue preserving contrast enhancement
function. The transformation is general in the sense that
the function ’ ’ can be any contrast enhancement function used
for grey scale images and is gamut problem free irrespective of
the nature of the function ’ ’.