For multiprimary displays, color within the interior of the gamut can be reproduced with several different control values, a situation that is in contrast with the three primary scenario, where the control values are unique. For a given color, the selection of the control values, or color calibration, becomes a fundamental step for color rendition on multiprimary devices. Because spatially smooth variations in color are common in imagery and it is critical that despite device variations these be maintained as smooth variations in renditions, it is also desirable that the calibration strategy preserve smoothness of the device control values over color space. Based on this motivation, we propose a variational framework for color calibration of multiprimary displays that emphasizes smoothness by minimizing the squared norm of the gradient of the calibration function over the display gamut. We test our proposed methodology on a four primary system, and compare its performance with calibrations obtained from other standard methodologies. Results indicate that, compared with the alternatives, the proposed variational approach offers the smoothest variation in the control values over the entire color space and as a result also exhibits enhanced robustness in the presence of device variations.

We have developed a novel LED display with RGGB color architecture with 4sub-pixels rendering. Sub-pixel rendering is known as a method of the perceptual enhancement of conventional display resolution higher than normal pixel rendering. In this paper, LED light control filter algorithm is proposed in order to reduce the color fringe artifact by sub-pixel rendering. A new LED display which has RGGB 4 sub-pixel structure with filtered sub-pixel rendering is evaluated by comparing the simulated MTF and visual test of the displayed wedge pattern. The results show that it has 2 times higher perceptual resolution without color fringe artifact and it is possible to be about 30% cost cutting.

Transparent displays have received attention as next-generation displays. In this paper, a new method to estimate the luminance transition curve of the black-and-white patch located behind the transparent plastics is presented. The luminance transition curve can provide the information on the blurriness of the transparent displays. In addition, it can be utilized to simulate the perceived images on the transparent display. Experimental results indicate that the proposed method accurately estimates the luminance transition curve of the black-and-white patch.

Trilinear interpolation is a method of multivariate interpolation on a three-dimensional regular grid. It approximates the value of an intermediate point using data on the lattice points, and thus is frequently used for display characterization with 3D lookup tables (3D LUTs). However, large color errors are usually caused by the nonlinear relationship between the source RGB space and the destination CIELAB space. In this article the display characterization is improved by modifying the traditional trilinear interpolation model. First, the Yule–Nielsen n-factor is applied to the destination functions, for the purpose of reducing the nonlinearity between the source and destination color spaces. Afterward, different calibrating curves are developed to calculate the effective values of the source RGB values. The input/source RGB values are usually called nominal values, and the effective values can be regarded as the optimized RGB values which improve the matching degree of the predicted and measured destination CIELAB values. In experiment, a Toshiba M5 liquid crystal display is characterized by using the modified trilinear interpolation model, and the forward and inverse characterization errors of different methods are calculated and compared. The evaluation results demonstrate that both the average and the maximum color errors have significantly decreased when calibrating curve III (one of the three types of curves developed) is employed in combination with the optimal n-factor. Thus, the method of developing effective calibrating curves and finding optimal n-factors proposed in this article can be adopted during display characterization. © 2016 Society for Imaging Science and Technology.

The preferred color temperature of a non-transparent display and an OLED transparent display was investigated. 24-inch LCD monitor was used to simulate both types of displays shown under two-different background color temperature (3000K and 6500K) conditions. Twenty observers participated the psychophysical experiment in a dark room. They were asked to choose the most preferred display image among the images having 9 different color temperatures. The results showed that as the color temperature of the surround decreases, the preferred color temperature of the monitor also decreases. Also it is found that the preferred color temperature of the total white (the monitor white plus transmitted light) of OLED transparent display is similar with that of the non-transparent display.

A remarkably simple color constancy method was recently developed, based in essence on the Gray-Edge method, i.e., the assumption that the mean of color-gradients in a scene (or colors themselves, in a Gray-World setting) are close to being achromatic. However this new method for illuminant estimation explicitly includes the important notions that (1) we cannot hope to recover illuminant strength, but only chromaticity; and (2) that a polynomial regression from image moment vectors to chromaticity triples should be based not on polynomials but instead on the roots of polynomials, in order to release the regression from absolute units of lighting. In this paper we extend these new image moments in several ways: by replacing the standard expectation value mean used in the moments by a Minkowski p-norm; by going over to a float value for the parameter p and carrying out a nonlinear optimization on this parameter; by considering a different expectation value, generated by using the geometric mean. We show that these strategies can drive down the median and maximum error of illumination estimates.

Direct Binary Search (DBS), as one of the three categories of halftoning, provides the best, visually pleasing halftoning quality. However, as a sequential algorithm, DBS is most computational complex so it always plays the role of offline algorithm for other halftoning categories (like tone dependent error diffusion, hybrid screen, etc.). Meanwhile, it is seldom directly works as a real-time/online solution for current commercial printers. In this paper, we would like to present a parallel version DBS with same image quality compared with original DBS, which can fit the current Same Instruction Multiple Data (SIMD) system, like General-Purpose Graphics Processing Unit (GP-GPU), and furthermore, there will be the potential that DBS can work on current multi-core system as real-time solution for halftoning.

In this paper, we look into the superposition of two periodic clustered-dot color halftones, which are widely used for electrophotographic printers due to their print stability. The scope of our research lies in understanding how to make the best color assignments to the two regular or irregular halftones in order to minimize the perceived error. We develop a model that agrees with a human observer and allows fast implementation. In order to account for the difference in the responses of the human viewer to luminance and chrominance information, we use the Y_y C_x C_z color space, which is a linearized version of the L*a*b* uniform color space. The perceived error helps us identify the configuration of colors and screens that will improve the appearance of the superposition image. We believe that making the right color assignments is essential for developing high quality color images.

Digital cameras capture images through color filter array patterns and reconstruct the images using an appropriate demosaicking algorithm. CFAs usually contain three primary color filters. Since the panchromatic/ white filter receives less noise compared to the Red, Green and Blue filters, the CFA also can have additional white filters to reduce the noise impact on the reconstructed color image. Digital cameras only receive one color component at each pixel location through the CFA and the other unknown color components will be estimated using the demosaicking algorithm. In this paper, the RGBW-Bayer pattern has been studied, and appropriate adaptive and non-adaptive demosaicking algorithms have been provided for it. Also an optimized way will be presented to estimate the panchromatic filter output using red, green and blue color information. A modified demosaicking algorithm also has been presented for a new RGBW CFA[1], and the comparison between these two RGBW CFAs and the RGBw-Kodak[9] CFA has been provided. The proposed algorithms have been tested on the Kodak sample images.