Image quality analysis of a color LCD as well as a monochrome LCD using a Foveon color CMOS camera

Abstract

We have combined a CMOS color camera with special software to compose a multi-functional image-quality analysis instrument. It functions as a colorimeter as well as measuring modulation transfer functions (MTF) and noise power spectra (NPS). It is presently being expanded to examine fixed-pattern noise and temporal noise. The CMOS camera has 9 μm square pixels and a pixel matrix of 2268 x 1512 x 3. The camera uses a sensor that has co-located pixels for all three primary colors. We have imaged sections of both a color and a monochrome LCD monitor onto the camera sensor with LCD-pixel-size to camera-pixel-size ratios of both 12:1 and 17.6:1. When used as an imaging colorimeter, each camera pixel is calibrated to provide CIE color coordinates and tristimulus values. This capability permits the camera to simultaneously determine chromaticity in different locations on the LCD display. After the color calibration with a CS-200 colorimeter the color coordinates of the display's primaries determined from the camera's luminance response are very close to those found from the CS-200. Only the color coordinates of the display's white point were in error. For calculating the MTF a vertical or horizontal line is displayed on the monitor. The captured image is color-matrix preprocessed, Fourier transformed then post-processed. For NPS, a uniform image is displayed on the monitor. Again, the image is pre-processed, transformed and processed. Our measurements show that the horizontal MTF's of both displays have a larger negative slope than that of the vertical MTF's. This behavior indicates that the horizontal MTF's are poorer than the vertical MTF's. However the modulations at the Nyquist frequency seem lower for the color LCD than for the monochrome LCD. The spatial noise of the color display in both directions is larger than that of the monochrome display. Attempts were also made to analyze the total noise in terms of spatial and temporal noise by applying subtractions of images taken at exactly the same exposure. Temporal noise seems to be significantly lower than spatial noise.