Implementation And Optimization Of The Multi-Channel Display System

Currently, due to the limitations of present technology, manufacturing cost and other factors, multi-screen display is still the main approache to realize large screens. Since the color difference between different screens is universe, color uniformity of multi-screen display systems become the key issue affecting their display quality.According to LCD screen display, the paper discussed the main approaches to realize multi-screen display and their advantages and disadvantages. And choosing a multi-channel single graphics mode as the main research object, the paper proposes a method to improve the color uniformity. Based on the measured performance parameters of the screens, a virtual color space is defined. The gamut of the virtual color space is in the overlap area of the all screens' color gamuts, and the data needed contains chromaticity coordinates and brightness gamma curves of the three primary colors and the white color of the virtual space. And by the conversion relationship between the virtual color space and color spaces of different screens, the conversion method of videos'gray scale data can be determined, which makes that each screen's color space displayed will be changed to the virtual color space defined. Next, the paper proposes processing the video data built on the hardware of the multi-channel system through OpenGL programming to implement the algorithm. Finally, we measure the screens which are processed by the algorithm for improving color uniformity. At the white color the color difference is decreased from 5.2 to 1.37, indicating that the algorithm can improve the color uniformity of the screens.Since when the virtual color space is defined, some parts of the gamuts are losed, this paper presents reducing the color gamut losses through the color gamut compression matching algorithm, and analyzes the process of matching two different gamut, and achieve different color gamut matching algorithm through software simulation. In order to judge the differences among the effects of the different matching algorithm, this article designs a subjective experiment, which shows images modified by different algorithms to the subjects, and lets the subjects rate. ultimately we conclude that the effects of gamut mapping algorithms is related to pictures, and we need to select the most appropriate gamut mapping algorithm according to the pictures'content.