In digital cinema, an image goes through many types of processes like scanning, mastering, and digital intermediate. Among them, the digital intermediate process plays a central role because it determines the final color of an image. It edits and changes the colors of the images. However, some color distortions such as color bleeding are generated when editing and changing local colors in an image. In this paper, local color improvement for digital intermediate is proposed based on color transfer. Our method is simple and efficient color improvement that does not requires neither precise image segmentation nor feature matching. To prevent color distortions, a modified color influence map is proposed with color categories. First, the source image is roughly segmented using a color category map, which groups similar colors in color space. Second, the color influence map is modified by assigning different weights to the lightness and chroma components. Lastly, the modified color influence map and color category map filtered with anisotropic diffusion are combined. Experimental results show that the proposed method produces less color distortion in the resulting image.

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.

A method of identifying JPEG 2000 images with different coding parameters, such as code-block sizes, quantization-step sizes, and resolution levels, is presented. It does not produce false-negative matches regardless of different coding parameters (compression rate, code-block size, and discrete wavelet transform (DWT) resolutions levels) or quantization step sizes. This feature is not provided by conventional methods. Moreover, the proposed approach is fast because it uses the number of zero-bit-planes that can be extracted from the JPEG 2000 codestream by only parsing the header information without embedded block coding with optimized truncation (EBCOT) decoding. The experimental results revealed the effectiveness of image identification based on the new method.

In this paper, we propose a CUDA implementation of DWT for JPEG 2000 codec. We show that the performance of JPEG 2000 codec implemented by CUDA is better than CPU based implementation. The performance of the DWT implemented by CUDA is achieved 27.7 frame/second in 4K digital cinema.

This paper shows the effectiveness of a cinematographic camera for controlling 3D video by measuring its effects on viewers with several typical camera works. 3D free-viewpoint video allows us to set its virtual camera on arbitrary positions and postures in 3D space. However, there have been neither investigations on adaptability nor on dependencies between the camera parameters of the virtual camera (i.e., positions, postures, and transitions) nor the impressions of viewers. Although camera works on 3D video based on expertise seems important for making intuitively understandable video, it has not yet been considered. When applying camera works to 3D video using the planning techniques proposed in previous research, generating ideal output video is difficult because it may include defects due to image resolution limitation, calculation errors, or occlusions as well as others caused by positioning errors of the virtual camera in the planning process. Therefore, we conducted an experiment with 29 subjects with camera-worked 3D videos created using simple annotation and planning techniques to determine the virtual camera parameters. The first point of the experiment examines the effects of defects on viewer impressions. To measure such impressions, we conducted a semantic differential (SD) test. Comparisons between ground truth and 3D videos with planned camera works show that the present defects of camera work do not significantly affect viewers. The experiment's second point examines whether the cameras controlled by planning and annotations affected the subjects with intentional direction. For this purpose, we conducted a factor analysis for the SD test answers whose results indicate that the proposed virtual camera control, which exploits annotation and planning techniques, allows us to realize camera working direction on 3D video.

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.

We developed an olfactory display to blend 8 component odors at any composition. The solenoid valves controlled by an algorithm with delta sigma modulation showed the sufficient capability. Then, we developed a system for presenting a movie together with scents. We actually made a movie with scents and evaluated it using questionnaire survey. It was found that the scene with smell attracted the experimental subjects' attention and, moreover, the contrast of the pleasant smell with the offensive one emphasized their attention. Furthermore, we established several guidelines for producing movies with scents.

JPEG2000, an international standard for still image compression, offers 1) high coding performance, 2) unified lossless/lossy compression, and 3) resolution and SNR scalability. Resolution scalability is an especially promising attribute given the popularity of Super High Definition (SHD) images like digital-cinema. Unfortunately, its current implementation of resolution scalability is restricted to powers of two. In this paper, we introduce non-octave scalable coding (NSC) based on the use of filter banks. Two types of non-octave scalable coding are implemented. One is based on a DCT filter bank and the other uses wavelet transform. The latter is compatible with JPEG2000 Part2. By using the proposed algorithm, images with rational scale resolutions can be decoded from a compressed bit stream. Experiments on digital cinema test material show the effectiveness of the proposed algorithm.

In virtue of great progress in computer graphics technologies, CG movies have been getting popular. However, cinematography techniques, which contribute to improving the contents' comprehensibility, need to be learned from professional experiences, and not easily acquired by non-professional people. This paper focuses on film cutting as one of the most important cinematography techniques in conversational scenes, and presents a system that automatically generates shot transitions to improve comprehensibility of CG contents. First, we propose a cognitive model of User Involvement serving as constraints on selecting shot transitions. Then, to examine the validity of the model, we analyze shot transitions in TV programs, and based on the analysis, we implement a CG contents creation system. Results of our preliminary evaluation experiment show the effectiveness of the proposed method, specifically in enhancing contents' comprehensibility.

Lossless video coding is required in the fields of archiving and editing digital cinema or digital broadcasting contents. This paper proposes multiresolution lossless video coding using a discrete wavelet transform and adaptive inter/intra-frame prediction in the wavelet domain. The multiresolution structure based on the wavelet transform facilitates interchange among several video source formats such as Super High Definition (SHD) images, HDTV, SDTV, and mobile applications. In order to increase the compression ratio, and to keep the computational cost low, the adaptive inter/intra-frame prediction is performed in the lowest wavelet transform domain. The adaptive inter/intra-frame prediction can adapt to changes in the local inter/intra-frame statistics. Experiments on digital cinema test sequences confirm effectiveness of the proposed algorithm.