Weighted Constrained Hue-Plane Preserving Camera Characterization

Color correction relates device dependent sensor responses (RGB) to device independent color values (XYZ). Here we present a new approach to Hue-plane Preserving Color Correction (HPPCC) using weighted constrained 3 × 3 matrices. Hue-plane preservation was introduced in [1] in conjunction with an HPPCC method. That method maps using a finite number of local white point preserving 3 × 3 matrices, each of which operates in a hue-angle delimited subregion of device space defined by the white and two adjacent chromatic training set colors. However, that formulation does not leave room for optimization or continuity beyond C⁰ in the transitions between the subregions. To remedy that our new method uses hue-angle specific weighted matrixing: given a device RGB from which a device hue-angle is derived, a corresponding transformation matrix is found as the normalized weighted sum of all precalculated constrained white point and training color preserving matrices. Each weight is calculated as a power function of the minimum difference between the device and the training color hue-angle. The weighting function provides local influence to the matrices that are in close hue-angle proximity to the device color. The power of the function is optimized for global accuracy. We call this Hue-plane Preserving Color Correction by Weighted Constrained Matrixing HPPCC-WCM ¹ 1. Experiments performed using different input spectra show that our method consistently improves on both stability and accuracy compared to state of the art methods.