LCD is a common display device. Due to the device dependence in color space, it is necessary to characterize LCD. In this paper, polynomial regression method is used to establish the color conversion model from RGB to CIEXYZ for colorimetric characterization of LCD, and black point correction is added to solve different polynomial parameters and compare the color difference. In the experiment, 17 groups of training samples were selected to solve the parameters and 200 groups of random test samples were used to verify the accuracy of the model. The experimental results show that the cubic polynomial curve model has the highest accuracy and the maximum chromatic aberration is 4.2962, which achieves better display effect.
Generative Adversarial Networks (GANs) is one of the most promising generative model in recently years. In this paper, we proposed a model called terrain maker Generative Adversarial Networks (TMGAN). It differs from the original GANs in three points: first, based on given topographic map, TMGAN can generate corresponding satellite aerial map, and vice versa. Second, TMGAN can modeled the terrain adaptively. Third, TMGAN can predict the height map of surface environment. We collected two data sets of paired and unpaired topographic maps and satellite aerial maps to train our model and test the influence of hidden variables. In this paper, we demonstrate the three-dimensional modeling ability of TMGAN.
Colorimetric characterization can reduce the distortion of image color information in the process of reproduction of the display device, so as to ensure that the same image can be accurately transmitted and reproduced. In order to realize the precise color characteristics of LCD, this paper uses the steepest descent method to optimize the parameters of GOG model, and establishes the color space conversion model from RGB to CIEXYZ and analyzes the model accuracy. The experimental results show that the maximum color difference of the model is 4.7494, and the average color difference is 2.7435, which can meet the accuracy needs of LCD colorimetric characterization.
In order to solve the problem that the same image has different display results on different monitors, the color characteristic of the display is needed. In this paper, the least square method is used to fit the experimental data，the polynomial regression method is used to build the RGB to CIEXYZ color conversion model of the display, and the accuracy of the model is analyzed. The experimental results show that the accuracy of the cubic polynomials curve model is the highest, the maximum color difference is 5.2862, and the average color difference is 2.6510.
Black point is the point at which RGB's single channel digital drive value is 0. Due to the problem of light leakage of liquid-crystal displays (LCDs), black point’s luminance value is not 0, this phenomenon bring some errors to colorimetric characterization of LCDs, especially low luminance value driving greater sampling effect. This paper describes the characteristic accuracy of polynomial model method and the effect of black point on accuracy, the color difference accuracy is given. When considering the black point in the characteristics equation, the maximum color difference is 3.246, the maximum color difference than without considering the black points reduced by 2.36. The experimental results show that the accuracy of LCDs colorimetric characterization can be improved, if the effect of black point is eliminated properly.
The colorimetric characterization of the display can achieve the purpose of precisely controlling the color of the monitor. This paper describes an improved method for estimating the gamma value of liquid-crystal displays (LCDs) without using a measurement device was described by Xiao et al. It relies on observer’s luminance matching by presenting eight half-tone patterns with luminance from 1/9 to 8/9 of the maximum value of each color channel. Since the previous method lacked partial low frequency information, we partially replaced the half-tone patterns. A large number of experiments show that the color difference is reduced from 3.726 to 2.835, and our half-tone pattern can better estimate the visual gamma value of LCDs.
Image quality evaluation is a classic research topic, the goal is to design the algorithm, given the subjective feelings consistent with the evaluation value. This paper mainly introduces several typical reference methods of Mean Squared Error(MSE), Peak Signal to Noise Rate(PSNR), Structural Similarity Image Metric(SSIM) and feature similarity(FSIM) of objective evaluation methods. The different evaluation methods are tested by Matlab, and the advantages and disadvantages of these methods are obtained by analyzing and comparing them.MSE and PSNR are simple, but they are not considered to introduce HVS characteristics into image quality evaluation. The evaluation result is not ideal. SSIM has a good correlation and simple calculation ,because it is considered to the human visual effect into image quality evaluation,However the SSIM method is based on a hypothesis,The evaluation result is limited. The FSIM method can be used for test of gray image and color image test, and the result is better. Experimental results show that the new image quality evaluation algorithm based on FSIM is more accurate.
In order to improve the accuracy of colorimetric characterization of liquid crystal display, tone matrix model in color management modeling of display characterization is established by using constrained least squares for quadratic polynomial fitting, and find the relationship between the RGB color space to CIEXYZ color space; 51 sets of training samples were collected to solve the parameters, and the accuracy of color space mapping model was verified by 100 groups of random verification samples. The experimental results showed that, with the constrained least square method, the accuracy of color mapping was high, the maximum color difference of this model is 3.8895, the average color difference is 1.6689, which prove that the method has better optimization effect on the colorimetric characterization of liquid crystal display.
A new single image super-resolution method based on self-similarity across different scales and pyramid model is proposed. In order to enrich the diversity of the training patches but not increase the computational complexity, we rotate the low resolution input image by a certain angle from 0° to 90° and down-sample them into 2 layers pyramid model respectively. However, most self-similarity super-resolution algorithms was carried out by the fixed size of patch. So, in this paper we observe the effect of patch size using the various patch size then pick out the most appropriate patch size. During the mapping process, we use the Fast Library for Approximate Nearest Neighbors (FLANN) to search the corresponding nine closest patches in high-frequency pyramid then carry out Gaussian weighted (SSD), which can avoid the occasionality and mismatch by using the nearest neighbor strategy. Finally, the local constraint and the iterative back projection algorithm are adopted to optimize the reconstructed image. Experimental results validate that the algorithm is better than the traditional algorithm in visual effects and computational complexity.
In this paper, a new method based on machine vision is proposed for the defects of the traditional manual inspection of the quality of printed matter. With the aid of on line array CCD camera for image acquisition, using stepper motor as a sampling of drive circuit. Through improvement of driving circuit, to achieve the different size or precision image acquisition. In the terms of image processing, the standard image registration algorithm then, because of the characteristics of CCD-image acquisition, rigid body transformation is usually used in the registration, so as to achieve the detection of printed image.
In liquid crystal display (LCD) colorimetric characterization, it needs to convert RGB the device-dependent color space to CIEXYZ or CIELab the device-independent color space. Namely establishing the relationship between RGB and CIE using the data of device color and the corresponding data of CIE. Thus a color automatic message acquisition software is designed. We use openGL to fulfill the full screen display function, write c++ program and call the Eyeone equipment library functions to accomplish the equipment calibration, set the sample types, and realize functions such as sampling and preservation. The software can drive monitors or projectors display the set of sample colors automatically and collect the corresponding CIE values. The sample color of RGB values and the acquisition of CIE values can be stored in a text document, which is convenient for future extraction and analysis. Taking the cubic polynomial as an example, each channel is sampled of 17 sets using this system. And 100 sets of test data are also sampled. Using the least square method we can get the model. The average of color differences are around 2.4874, which is much lower than the CIE2000 commonly required level of 6.00.The successful implementation of the system saves the time of sample color data acquisition, and improves the efficiency of LCD colorimetric characterization.