6533b82efe1ef96bd1293275

RESEARCH PRODUCT

High-end colorimetric display characterization using an adaptive training set

subject

description

A new, accurate, and technology-independent display color-characterization model is introduced. It is based on polyharmonic spline interpolation and on an optimized adaptive training data set. The establishment of this model is fully automatic and requires only a few minutes, making it efficient in a practical situation. The experimental results are very good for both the forward and inverse models. Typically, the proposed model yields an average model prediction error of about 1 ∆Eab* unit or below for several displays. The maximum error is shown to be low as well. freedom given to the model considering the choice of a tar- get color space and of the kernel and smoothing factor for the interpolation. This increases noticeably the accuracy of the model. The inverse model is based on a tetrahedral in- terpolation, using a grid designed in RGB. As design goals, we aim for the display color-characterization model to be as accurate as possible on any type of display and we want the color correction to be done in real time (no pre-processing). Moreover, we want the model establishment not to exceed a practical time of a few minutes (the time of a coffee break). We first present the state of the art of display color characterization in Sec. 2. We then introduce our new accu- rate display color-characterization model. We evaluate this method experimentally on different displays. Before con- cluding, we describe briefly its application to multispectral image real-time color rendering under a virtual illumination through its GPU implementation.