To compute a color characterization of a scanner for a particular medium, or to compute a color calibration of a printer using a scanner, an array of patches may be measured (using a scanner). The measurements of those patches, however, are affected by an integrating cavity effect (ICE). Therefore, the measurements do not accurately predict the reflectance of the page. As such, there is a desire to avoid the impact of integrating cavity effect (ICE), in a manner that takes into account the fact that patches are being processed.
By way of background, the adverse impact of the integrating cavity effect (ICE) in scanners has been identified. Keith Knox, “Integrating cavity effect in scanners”, Proceedings on IS&T/OSA Conference on Optics and Imaging in the Information Age, Rochester, pp. 156-158 (1996), the disclosure of which is incorporated herein by reference in its entirety. In this regard, the integrating cavity effect (ICE) makes it appear that measured pixel values are closer to the values of their neighbors than if the reflectance values were independently measured. More particularly, when a target image is scanned, part of the light from the scanner that is reflected off the page is reflected back to the page because the cavities of the light emitting elements of the scanning device are typically reflective. Accordingly, the reflectance of the local region—not just the target of interest—impacts the apparent illumination. If this is not taken into account when measuring the scanner response to printed targets (whether for characterizing the scanner or a printer), unnecessary errors (likely to appear as noise) are introduced into the data. Integrating cavity effect does not affect all scanners; however, it is common on lower cost scanners, as the mirror responsible for the effect also reduces the power requirements of the lamp.
Knox's method, simply put, is to filter the full resolution raster image with a large averaging kernel, and use the filtered image in a formula expressing the real reflectance in terms of the measured reflectance at a pixel, the average reflectance in the vicinity of that pixel, and a single parameter. Knox requires that the average image changes slowly, which is generally a good assumption if the average is taken over a large enough area relative to the resolution.
Along these lines, previous approaches to address the adverse impact of the integrating cavity effect have taken two forms: changing the printed target or applying a raster based correction. Changing the printed target includes grouping similar colors together and repeating patches to effectively randomize surroundings. Knox provides a raster based approach, which requires a large filter and depends on the local average of reflectance values changing very slowly. Neither of these approaches gives a completely satisfactory result, however.