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SilverFast
Colour Management Tutorial
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CMS-Tutorial E 230106.qxd6
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SilverFast
Copyright
Copyright © 1994-2006 SilverFast®, LaserSoft Imaging™AG, Germany
No part of this publication may be reproduced, stored in a retrieval
system, or transmitted, in any form or by any means, electronic,
mechanical, or otherwise, without the prior written permission of
LaserSoft Imaging™ AG.
The software applications SilverFast®Ai, SilverFast® HDR, SilverFast®
SE, SilverFast® DC-VLT, SilverFast® DC Pro are copyrighted by LaserSoft Imaging™ AG and may only be used as stated in the license
agreement.
All mentioned trademarks are the protected trademarks of the
respective owners. SilverFast®Ai is a protected trademark of LaserSoft Imaging™ AG, Germany.
Tutorial written by John Ingraham
Editing by Karl-Heinz Zahorsky, Gerhard Wolff, Martin Münier and
Inga Ortmann.
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Contents
Table of Contents
1.0 Overview
6
2.0 Colour Theory
7-15
2.1 Visualization of Colour . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7
2.2 Defining Colour . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .8
2.3 Additive and Subtractive Colour Systems . . . . . . . . . . . . .8-9
2.4 Colour Spaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9-13
2.5 Colour Gamut . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14-15
3.0 Colour Conversion
16-20
3.1 Colour Conversion between Devices . . . . . . . . . . . . . . . . . .16
3.2 International Color Consortium - ICC . . . . . . . . . . . . . . . . . .16
3.3 ICC Colour Management Workflow . . . . . . . . . . . . . . . . . . .16
3.4 ICC Profiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .17
3.5 Profile Linking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18
3.6 Gamma Correction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .19
3.7 Rendering Intent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .19
3.8 ICC Profile Generation . . . . . . . . . . . . . . . . . . . . . . . . . . .20-21
4.0 SilverFast Colour Management Workflows
23-34
4.1 The CMS Panel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23
4.2 Input to Internal Workflow . . . . . . . . . . . . . . . . . . . . . . . .24-25
4.3 Embedded to Internal Workflow . . . . . . . . . . . . . . . . . . .26-27
4.4 Input to Internal with Monitor Profile Workflow . . . . . . .28-30
4.5 Input to Output Workflow . . . . . . . . . . . . . . . . . . . . . . . . .31-32
4.6 Input to Lab Workflow . . . . . . . . . . . . . . . . . . . . . . . . . . .33-34
5.0 SilverFast ICC Profile Generation
35-42
5.1 Gamma Correction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .35-37
5.2 SilverFast Colour Calibration Process . . . . . . . . . . . . . .38-42
6.0 Additional References
43
Books . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .43
Websites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .43
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Overview
1.0 Overview
This tutorial outlines the ICC colour management workflow within
SilverFast Applications and the procedures for creating ICC colour
profiles.
The tutorial is broken into 4 sections:
Section 2.0 provides a basic deion of colour theory
Section 3.0 outlines the ICC colour conversion workflow
Section 4.0 highlights the main colour management workflows
within SilverFast, and
Section 5.0 explains the process for creating ICC profiles using
SilverFast.
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This document assumes that the reader has some basic knowledge of the SilverFast products.
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2.0 Colour Theory
2.1 Visualization of Colour
The visualization of colour can be viewed as a three-part
process shown in Figure 2.1.
Light Source: Light is emitted from a light source. The light
source emits different amounts of light at various wavelengths.
Object: The light from the source is then placed onto an object.
The object in turn ively reflects and absorbs different
wavelengths coming from the light source.
Detector: The wavelengths of light that are reflected from the
object are then processed using some form of measurementdetection system.
Visualization Prozess
Figure 2.1
In the visualization process, the detector usually refers to the human visual
system. However, the optics, measurement detectors (CCD, CMOS arrays) and
associated electronics within a scanner or digital camera also represent another
type of detector. The human eye, scanners, and digital cameras are considered
trichromatic systems. This means that the measurement detectors contain three
different “sensors” that can perceive and differentiate between colours.
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2.2 Defining Colour
To define a colour, one needs to know three parameters (see
Figure 2.2):
Hue: The shade of the colour (e.g. red, green, blue)
Lightness: How light or dark the actual colour appears
Saturation: How dull or vivid a colour appears
Hue
2
Lightness
Saturation
Figure 2.2
2.3 Additive and Subtractive Colour Systems
Devices used to display or print images work by using an additive or subtractive colour system.
2.3.1 Additive Colour (Figure 2.3)
An additive colour device utilizes a combination of “lights” at
different wavelengths to generate a specific colour. The three
primary colours in an additive colour system are red, green, and
blue (RGB). In an additive colour system, the addition of red,
green, and blue lights white while the absence of light
s black. Mixing different percentages of the red, green,
and blue produces other colours. For example, the combination
of red and blue produces a magenta colour. Televisions and
computer monitors are the best-known additive colour devices.
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Figure 2.3
Figure 2.4
2.3.2 Subtractive Colour (Figure 2.4)
A subtractive colour device applies various amounts of
colourant (e.g. dyes, pigments) onto a medium (e.g. paper). The
colourants ively reflect or absorb light, which in turn,
the sensation of colour. The primary colours for a subtractive system consist of cyan, magenta, and yellow (CMY)
colourants and the combination of cyan, magenta, and yellow
colourants produce black. Applying different percentages of
cyan, magenta, and yellow s other colours. Digital printers
and photographic printers operate using a subtractive colour
system.
In some subtractive colour devices, an additional black
colourant (K) is also used. The Black colourant provides several
advantages:
The black colourant produces a purer black colour than can be
achieved using CMY alone,
Less ink needs to be placed on the medium, which improves
image quality and reduces ink costs.
It is important to note that many printers accept data in RGB
format. Printer driver software then mathematically s the
RGB image data into CMYK for printing.
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2.4 Colour Spaces
2.4.1 Device Dependent and Device Independent Colour Spaces
A Colour Space can be defined as a method for systematically
organizing colours for visualization and communication.
Colour Spaces are divided into three categories as shown in
Table 2.1:
Device Dependent: Device dependent colour spaces define
colour for a given imaging device. Examples of device dependent colour spaces include RGB and CMYK.
2
The advantage of working with a device dependent colour
space is that the data can be easily obtained from the device
and used in many software applications (e.g. web sites, graphics applications, word processors, etc.). This is especially true
for RGB images. However two imaging devices, such as two
scanners, can produce different RGB values for a given original.
For this reason, device dependent colour spaces do not provide
enough information to actually define a specific colour.
Device Independent: These colour spaces consist of mathematical representations of colour that are independent of an imaging device. Examples of device independent colour spaces
include CIE XYZ, CIE Lab.
The advantage of using a device independent colour space is
that colours can be easily quantified.
The obvious disadvantage is that only a few software applications can actually work with device independent colour spaces.
Moreover, if you wish to display or print an image in a device
independent colour space you still have to it back to a
device dependent colour space.
Internal Colour Spaces (Working Colour Space): Internal or
working colour spaces are a cross between device dependent
and device independent colour spaces. To an internal
colour space, a mathematical transformation is done to
device independent colour information to a standard set of
RGB values. This essentially calibrates the RGB values. Examples of internal colour spaces include Adobe RGB and sRGB.
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Internal colour spaces provide two main advantages. First they
produce image data that can easily be handled by imaging
software similar to the device dependent colour data. Secondly,
they accurately define a colour under a specific set of conditions. These two factors are very convenient for users who wish
to store images in a common colour space. The main disadvantage is that colour images still need to be ed back and
forth between a device dependent colour space and the working colour space.
Device Dependent
C
