| Research Abstract |
This research has been addressed to develop an Image-dependent Gamut Mapping Algorithm (GMA) across the different color media focusing on the following five major items.
(A) Basic design of nonlinear gamut mapping model based on the concept of Image-dependence.
(B) Development of 3D Image-to-Device Gamut Mapping Algorithm (3D I-D GMA)
c Research on Gamut Expansion Algorithm for narrow gamut images.
(D) Research on Pleasant Color Transform Algorithm by key color extraction from image.
(E) Development of compact 3D Gamut Boundary Descriptor (GBD) for image and its application to 3D I-D GMA
Our R&D results during 2000, 2001, and 2002 are summarized in (1)〜(3), (4)〜(6) and (7)〜(9), respectively as follows.
(1) Conceptual model of Image-dependent GMA and Hue-divided nonlinear 2D I-D GMA
(2) Automatic formation of 3D Image Gamut Shell Surface
(3) Description of smoothed 3D Gamut Shell Surface by Overhauser Spline Function
(4) Mapping Experiments by the proposed 3D I-D GMA
(5) Compact 3D Gamut Boundary Descriptor (GBD) by r-image method
(6) Gamut expansion algorithm based on Gaussian Histogram Specification
(7) Pleasant color conversion by Principal Component Matching in segmented colored areas
(8) Compression of 3D r-image GBD by SVD and Wavelet image compression techniques
(9) Psychophysical experiments on 3D I-D GMA using r-image GBD
In conclusion, 3D I-D GMA resulted in the better performance than the conventional 2D D-D GMA, Clipping GMA, and typical 3D D-D GMAs. The proposed I-D GMA worked very well especially for the wide-gamut CG image with highly saturated continuous tone. Besides, a novel GBD by r-image method was very useful for the quick comparison of the gamut sizes between image and device.
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