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 proposes a design method for representing monochrome medical X-ray images on an electronic display. The required quantizing resolution of the input density and output voltage are theoretically clarified. The proposed method makes it easier to determine the required quantizing resolution which is important in a X-ray diagnostic system.

This paper discusses the bit-rate compression of super high definition still images with subband coding. Super high definition (SHD) images with more than 20482048 pixels or resolution are introduced as the next generation imaging system beyond HDTV. In order to develop bit-rate reduction algorithms, an image evaluation system for super high definition images is assembled. Signal characteristics are evaluated and the optimum subband analysis/synthesis system for the SHD images is clarified. A scalar quantization combined with run-length and Huffman coding is introduced as a conventional subband coding algorithm, and its coding performance is evaluated for SHD images. Finally, new coding algorithms based on block Huffman coding and entropy coded vector quantization are proposed. SNR improvement of 0.5 dB and 1.0 dB can be achieved with the proposed block Huffman coding and the vector quantization algorithm, respectively.

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.

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.