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Last Modified: 2:46pm 19 Apr 12
|The following images demonstrate some of the concepts that are addressed in the research being performed within MCSL. Please remember that these images are designed to show concepts in a relative sense. Actual colors on your display will not match the colors of the original images.
Chromatic adaptation refers to the ability of the human visual system to compensate for changes in the prevailing color of the viewing environment. These two images can be used to demonstrate the effect.
First view the image of the fruit basket and note that half of the image is too blue while the other half is too yellow. Next stare at the black spot in the center of the adapting image (blue and yellow patches) for 30 seconds without letting your eyes wander. After the 30 seconds are up, look at the black spot in the center of the fruit basket image. You should notice a change in color appearance in the two halves of the field should nearly match.
By staring at the adapting image for 30 seconds, you have temporarily changed the color responses of those areas of your visual system through chromatic adaptation.
|Scanner Colorimetric Characterization
The first step in accurate cross-media color reproduction is knowing just what colors are present on an image for a given set of signals produced by an input device or used to drive an output or display device.
The images at left show the importance of this by contrasting the image produced by displaying raw RGB values from an image scanner with that produced after accurate colorimetric characterization of the scanner.
||Visual Encoding of Color
The human visual system does not process color images as three RGB or CMY color separations as is typical for color imaging systems.Instead, the human visual system decomposes color information into a
luminance channel that contains the "black-and-white" information in the scene and two chrominance channels that contain the hue and saturation information.
The luminance channel contains most of the spatial information in a scene, thus the human visual system encodes this information with a higher resolution than the chrominance channels. This is very similar to encoding schemes that are used in color television, jpg image compression, and the PhotoCD system.
These images illustrate the information content in a typical scene broken down into its luminance and chrominance components. Note the lack of fine detail in the chrominance image.
|Effect of Surround on Image Color Appearance
Images viewed in different surrounds appear different. For example, prints are usually viewed in light surrounds while projected slides are viewed in dark surrounds. When an image is viewed in a dark surround, it appears to be of lower contrast and saturation.
To offset this perceptual effect, images intended to be projected in a darkened room are produced to have higher physical contrast and saturation than images intended for viewing in a light surround. The images below illustrate the magnitude of this effect.
The required slide image illustrates the changes required to reproduce the appearance of the print image assuming that the print image was viewed in a light surround and the required slide image was viewed in a dark surround.
One of the most challenging problems in cross-media image reproduction is dealing with mismatches between the gamuts of various devices. An imaging device's gamut is the range of colors that particular device can produce. The images below illustrate two views of a three dimensional rendering of two device gamuts in the CIELAB color space. The wireframe gamut is that of a typical CRT monitor and the shaded gamut is that of a typical dye-diffusion thermal-transfer printer. Note that each device is capable of producing colors that cannot be obtained with the other device.
Last Modified: 2:46pm 19 Apr 12