Color image processing to convert an image into a printable image, that is an image capable of being printed, invariably involves some form of color and data transformation to convert the pixels of the color image into a printable image comprising a plurality of printable pixels, that is a pixel capable of being printed, defined by the colors of the printing device.
This conversion may be achieved by use of a lookup table to map the colors of the image into the colors of the printable image. In order to achieve accurate conversion and consistency between printing elements (such for example printheads or elements of a printhead) of the printing device, the colors printable by the printing device are calibrated and the lookup table is populated based on the calibration.
For a more complete understanding, reference is now made to the following description taken in conjunction with the accompanying drawings in which:
a and 7b illustrate a representation of an example of creating the transformation function;
In printing system, such as for example, a Page-Wide Array (PWA) printing system having a plurality of neighbouring printing elements which print across the media in bands, any differences in the colors generated by each printing element may become visible to the human eye as the colors are adjacent in bands making any difference, however slight, noticeable. Therefore, such printing systems impose very low color difference thresholds. As a result a more accurate color transform is required.
Prior solutions in the industry attempt to define the color transform through a general function not bounded by spatial constraints, such as a polynomial or a biharmonic operator. Such approaches lead to successful interpolations on those points that lie within the mesh of the transformation-defining points. However, the transformation of points outside the transformation domain is merely driven by the extrapolation of the behavior in the interior. The problem is that such extrapolation is likely to rapidly diverge and to provide non-accurate positioning of point in the destination space.
One type of prior solution to this is the usage of a tessellation to perform the transformation. However, it is unclear how the tessellation is defined (and furthermore there are no references on whether a gamut boundary is explicitly defined), and also there appears to be no solution of transforming the points outside of the hull.
Another solution for obtaining a highly detailed gamut description is obviously printing and measuring a large number of patches. The drawback is the large number of media real state and measurement times required to get a certain level of accuracy, which makes the method unfeasible for PWA printing systems.
The challenge comes when such accurate calibration is to be done on a reduced set of calibration patches, so that the procedure minimizes time and media waste. Note that, for a PWA printer, each die (or, in some cases, each die portion) counts as an independent printer to be calibrated. This fact multiplies the number of patches to be printed and measured.
Further, the use of a tessellation to perform the transformation can not be used to transform the points outside of the hull as there appears to be no explicit definition of the gamut boundary.
Another solution for obtaining a highly detailed gamut description is obviously printing and measuring a large number of patches. The drawback is the large number of media real state and measurement times required to get a certain level of accuracy, which makes the method unfeasible for PWA printers.
It is assumed that the gamuts of the printing systems (or dies) under consideration are similar in shape. This assumption is also made by existing one-dimensional, per-ink solutions.
In one implementation, an image 104 is uploaded to the computing device 102 using input device 108. In other implementations, the image may be retrieved from a previously generated image set contained on a storage media, or retrieved from a remote storage location, such as an online application, using the Internet. Image 104 may be a still digital image created by a digital camera, a scanner, or the like. In other implementations the image may be a moving image such as a digital video. Image 104 may be sent to an output device such as printing device 108 by the computing device 102. Other printing devices that may be used include, but are not limited to, a dot-matrix printer, an inkjet printer, a laser printer, line printer, a solid ink printer, and any other kind of digital printer. In other implementations, the image may be displayed to a user on an output device 108 including, but not limited to, a TV set of various technologies (Cathode Ray Tube, Liquid Crystal Display, plasma), a computer display, a mobile phone display, a video projector, a multicolor Light Emitting Diode display, and the like. The printing device 108 comprises a plurality of printing elements, for example, multiple arrays of ink nozzles for depositing ink onto a printing media 116.
In one implementation, the printing system 100 comprises image processing apparatus 110. The image processing apparatus 110 may be integral with the computing device 102 or the printing device 108. The image processing apparatus 110 includes a color calibration apparatus 120.
The color calibration apparatus 120 for calibrating the plurality of printing elements of the printing device 108 is shown in
Operation of the color calibration apparatus 120 is described with reference to
First, a reference gamut is retrieved from the storage device 209 by the processor 201. This may be an arbitrary gamut 500 (as illustrated in
Reduction of the reference gamut 500 is achieved by projecting each point to a semi segment that goes from white to a medium gray as illustrated by the arrows 507 shown in
The process of build a highly detailed description of the printing device 108 to calibrate involves a transformation 305 of the highly-detailed reference gamut so that it coincides with the element gamut points location.
The transformation function maps the first gamut volume into the element volume, using the few element gamut calibration points as anchors. A resulting second gamut volume is obtained as shown in
The transformation input space 611 of the first gamut volume 801 is divided in a regular tetrahedral grid as illustrated in
For points inside the second gamut volume, 409, a tessellation-based transform is used, 413. For points outside of the second gamut volume, as shown in
As a result the transformation function explicitly defines a boundary between the interior and the exterior of the transformation hull, and that different methods are used to transform points in each of the domains to create the mappings. The transformation methods of tessellation-based interpolation or the dihedral-angle based extrapolation are merely examples and it can be appreciated that other techniques may be used as alternatives.
The transformation function that creates second gamut volume is then used to create the mapping 309 between the actual colors and those printed by the printing elements. This mapping may be stored as a look-up-table (LUT) or the like.
This may be achieved by tessellating the second gamut volume and interpolating the position of the actions color within the second gamut volume tessellation to obtain the mapping to store in an LUT.
The result brings the gamut of a printing device to be calibrated as close as possible to the gamut of a “reference” printing device. The solution is commonly named 3D because it prints and measures points across the whole gamut space (which is three-dimensional, as opposed to Closed Loop Calibration (CLC) which does so only on primary colors in the ink space, which is one-dimensional).
Points forming a color gamut are transformed according to a transformation function providing significant improvements in accuracy while reducing the number of required calibration patches.
The fact that the method explicitly defines the boundary between the interior and exterior of the transformation hull allows the selection of the most convenient method for each region. The points outside the transformation hull are transformed with similar accuracy as the ones in the interior providing a method close to optimal.
A further benefit of the method is that it delivers a map of a given state of a printer/die onto a reference instead of being only an approximate, unbounded color space transformation. This results in greater gamut preservation and greater accuracy too.
Although various examples have been illustrated in the accompanying drawings and described in the foregoing detailed description, it will be understood that the present disclosure is not limited to the examples disclosed, but is capable of numerous modifications without departing from the scope of the present disclosure as set out in the following claims.
Filing Document | Filing Date | Country | Kind |
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PCT/EP2013/071564 | 10/15/2013 | WO | 00 |