Color signal decomposition method using 3-D Gamut boundary of multi-primary display

Abstract

Color signal decomposition method is to decompose the conventional three-primary colors (RGB) into the multi-primary control values of multi-primary display (MPD) under the constraints of tri-stimulus matching. For the satisfaction of tri-stimulus matching between input and output display systems, the MPD color signals have to be estimated from a device-independent color space such as CIEXYZ or CIELAB. However, as the target of MPD is to display moving-picture data, it is necessary to simplify the color space conversion between input and output systems and decomposition of the multi-primary control values. In this paper, color signal decomposition method for MPD is proposed using 3-dimensional look-up-table (3D-LUT) in linearized LAB space. The linearized LAB space satisfies the linearity and additivity in color space conversion and easily constructs the 3-D LUT considering lightness, chroma, and hue. For the reproduction of moving-picture data in MPD, the proposed method is based on 3-D LUT structure to reduce the complexity of hardware and processing time. First, 3-D LUT containing gamut boundary data of MPD is created to derive the multi-primary control values. The input images are transformed to linearized LAB values. Then, the corresponding color signals on the gamut boundary points, which have the same lightness and hue as the input point, are calculated. Also, the color signal for a point on the gray axis is calculated. Based on the gamut boundary points and a point on the gray axis, the MPD color signals for the input values can be obtained by interpolating between the gamut boundary points and a point on the gray axis. In particular, the neighboring gamut boundary points are used in the region of occurring abrupt signal change for a smooth change of hue. As a result, the proposed method guarantees computational efficiency and color signal continuity and requires less memory rather than conventional color decomposition methods.