A specification for digital cinema systems which deal with movies digitally from production to delivery as well as projection on the screens is recommended by DCI (Digital Cinema Initiative), and the systems based on this specification have already been developed and installed in theaters. The parameters of the systems that play an important role in determining image quality include image resolution, quantization bit depth, color space, gamma characteristics, and data compression methods. This paper comparatively discusses a relation between required bit depth and gamma quantization using both of a human visual system for grayscale images and two color difference models for color images. The required bit depth obtained from a contrast sensitivity function against grayscale images monotonically decreases as the gamma value increases, while it has a minimum value when the gamma is 2.9 to 3.0 from both of the CIE 1976 L* a* b* and CIEDE2000 color difference models. It is also shown that the bit depth derived from the contrast sensitivity function is one bit greater than that derived from the color difference models at the gamma value of 2.6. Moreover, a comparison between the color differences computed with the CIE 1976 L* a* b* and CIEDE2000 leads to a same result from the view point of the required bit depth for digital cinema systems.

This paper introduces a practical color filter array (CFA) interpolation technique. Among the many technologies proposed in this field, the inter-color methods that exploit correlation between color planes generally outperform the intra-color approaches. We have found that the filtering direction, e.g., horizontal or vertical, is among the most decisive factors for the performance of the CFA interpolation. However, most of the state-of-the-art technologies are not flexible enough in determining the filtering direction. For example, filtering only in the upper direction is not usually supported. In this context, we propose an inter-color CFA interpolation using a local map called unified geometry map (UGM). In this method, the filtering direction is determined based on the similarity of the local map data. Thus, it provides more choices of the filtering directions, which enhances the probability of finding the most appropriate direction. It is confirmed through simulations that the proposal outperforms the state-of-the-art algorithms in terms of objective quality measures. In addition, the proposed scheme is as inexpensive as the conventional methods with regard to resource consumption.

Acquisition of accurate colors is important in the modern era of widespread exchange of electronic multimedia. The variety of device-dependent color spaces causes troubles with accurate color reproduction. In this paper we present the outlines of accomplished digital camera system with device-independent output formed from tristimulus XYZ values. The outstanding accuracy and fidelity of acquired color is achieved in our system by employing an embedded color calibration system based on emissive device generating reference calibration colors with user-defined spectral distribution and chromaticity coordinates. The system was tested by calibrating the camera using 24 reference colors spectrally reproduced from 24 color patches of the Macbeth Chart. The average color difference (CIEDE2000) has been found to be ΔE = 0.83, which is an outstanding result compared to commercially available digital cameras.

To keep in step with the rapid progress of high quality imaging systems, the Digital Cinema Initiative (DCI) has been issuing digital cinema standards that cover all processes from production to distribution and display. Various evaluation measurements are used in the assessment of image quality, and, of these, the required number of quantization bits is one of the most important factors in realizing the very high quality images needed for cinema. While DCI defined 12 bits for the bit depth by applying Barten's model to just the luminance signal, actual cinema applications use color signals, so we can say that this value has an insufficient theoretical basis. This paper, first of all, investigates the required number of quantization bits by computer simulations in discrete 3-D space for the color images defined using CIE's XYZ signal. Next, the required number of quantization bits is formulated by applying Taylor's development in the continuous value region. As a result, we show that 13.04 bits, 11.38 bits, and 10.16 bits are necessary for intensity, density, and gamma-corrected signal quantization, respectively, for digital cinema applications. As these results coincide with those from calculations in the discrete value region, the proposed analysis method enables a drastic reduction in the computer simulation time needed for obtaining the required number of quantization bits for color signals.

Digital cinema will continue, for some time, to use image signals converted from the density values of film stock through some form of digitization. This paper investigates the required numbers of quantization bits for both intensity and density. Equations for the color differences created by quantization distortion are derived on the premise that the uniform color space L* a* b* can be used to evaluate color differences in digitized pictorial color images. The location of the quantized sample that yields the maximum color difference in the color gamut is theoretically analyzed with the proviso that the color difference must be below the perceivable limit of human visual systems. The result shows that the maximum color difference is located on a ridge line or a surface of the color gamut. This can reduce the computational burden for determining the required precision for color quantization. Design examples of quantization resolution are also shown by applying the proposed evaluation method to three actual color spaces: NTSC, HDTV, and ROMM.