<title>Image-dependent gamut mapping using a variable anchor point</title>

Abstract

Currently many devices reproduce electronic images in a variety of ways. However, the colors that are reproduced are different from the original color due to the differences in the gamut between devices. In this paper, an image dependent gamut mapping method is proposed. This method clips the chroma while compensating for the change oflightness caused by the lightness scaling required for a reproduction gamut. In this paper, the anchor point, which is the color center point in the mapping, is set at a lower point than the conventional mapping method. As a result, this reduces the difference between the original image on the monitor and the results on the reproduction device. Our mapping algorithm is applied to the gamut mapping between the monitor and printer. Consequently, the printer output image is highly consistent with the corresponding monitor image.

Spatial gamut mapping algorithms for cross‐display color reproduction

“…Hence, to achieve better gamut mapping, image-dependence approaches to GMAs need further study. 1,2 Thus far, the image-dependent algorithms that consider the image's spatial characteristics have become new technologies in the GMA field. These new types of GMAs, called spatial gamut mapping algorithms (SGMAs), are expected to result in more pleasing color matching than ever before.…”

Novel workflow for image-guided gamut mapping

“…We note that the current ICC profile standard is defined to allow storage of a number of gamut mappings, thus the suggested workflow is easily implemented without the need of redefining profiling standards. 7 Technical details are given in Appendix A.…”

“…This requires detection of the intersection of every mapping line with the source gamut and the destination gamut boundaries. [7][8][9][10] Note that these two steps, which are highly time consuming, are required of any gamut mapping algorithm, whether dependent or independent. In the image-dependent approach, it must be performed for each image, whereas in the independent approach, it is performed only once in a preprocess stage and used on all images.…”

“…Thus, image-dependent gamut mapping, which is dependent on the image gamut ͑the range of colors appearing in the image͒ and on the destination gamut, greatly improves image reproduction quality. 2,[7][8][9][10] However, industrial designers have rejected this approach due to the intense computations and extreme overhead in terms of run time compared to the imageindependent approach. In the never-ending quest for improving image quality, the industrial focus in recent years was on the improvement of the image-independent mapping algorithms.…”