We have introduced an extremely high resolution video system 'Super Hi-Vision' at the Kyushu National Museum. This feature opened in October 2005 with the purpose of exhibiting high-quality images of national treasures and traditional arts and crafts to its visitors. The system achieves high resolution using the spatial pixel offset method, quadrupling the horizontal and vertical resolution of HDTV. To display the images with high fidelity, it is important to manipulate the images on the basis of the system characteristics. This paper reports on the efforts to ensure image quality for this Super Hi-Vision System, focusing on resolution and color reproduction.

In this paper, we propose a new projector-based display which can perform the color simulator for print industry. The proposed color simulator can change the color of print by projecting the image onto the print. A color of print can be matched to the desired color by projecting the image which is calculated to minimize the color difference between the colors of target print and current print. This current print is measured by digital camera or digital scanner. Ideally, spectral camera or scanner is expected to be used for accurate color simulation on the current print, but it costs a lot for practical application. Therefore, in this paper, we compared two methods for color matching, one is the tristimulus-based method with XYZ tristimulus values and the other is the spectral-based method with spectral values. As the result of computer simulation, the average color difference ΔE *94 was 0.27 by the spectral-based method between the reflected radiance from the color of target print and the color of current print with projector, and the average color difference ΔE *94 was 2.09 by the tristimulus-based method. The efficiency of the proposed system is verified by the subjective evaluation between the target and current print with appropriate image projection.

A set of three optical filters was designed and a camera system was developed using these filters in order to capture high-fidelity colors within the gamut of vision. Photographs of a number of highly saturated colors and a combination of the Macbeth chart and 18 pieces of clothing samples of various colors were taken. A 39 matrix was used to convert the camera output signals into XYZ tristimulus data. The tristimulus values of the colors were compared with those of the images captured by the camera. The average color difference, ΔE, for these samples were found to be 2.16 and 1.18, respectively.

Gastric cancer is a great part of the cancer occurrence and the mortality from cancer in Korea, and the early detection of gastric cancer is very important in the treatment and convalescence. This paper, for the early detection of gastric cancer, proposes the analysis system of an endoscopic image of the stomach, which detects abnormal regions by using the change of color in the image and by providing the surface tissue information to the detector. While advanced inflammation or cancer may be easily detected, early inflammation or cancer is difficult to detect and requires more attention to be detected. This paper, at first, converts an endoscopic image to an image of the IHb (Index of Hemoglobin) model and removes noises incurred by illumination and, automatically detects the regions suspected as cancer and provides the related information to the detector, or provides the surface tissue information for the regions appointed by the detector. This paper does not intend to provide the final diagnosis of abnormal regions detected as gastric cancer, but it intends to provide a supplementary mean to reduce the load and mistaken diagnosis of the detector, by automatically detecting the abnormal regions not easily detected by the human eye and this provides additional information for diagnosis. The experiments using practical endoscopic images for performance evaluation showed that the proposed system is effective in the analysis of endoscopic images of the stomach.

Color correction needs to be performed to improve the quality of image/video production. The typical methods realize the color correction mainly in the spatial domain of RGB color space. In this paper, a linear color correction method in JPEG/MPEG-2 compressed domain is proposed. The correction is realized in the DCT domain of YUV color space without full-frame decompression. Experimental results show that the visual quality of the corrected images/videos in the compressed domain is identical to the quality of the images/videos corrected in the uncompressed domain.

To give comprehensive and consecutive understanding about load line regulation in the previous companion paper [1], more generalized expansion and theoretical derivation will be proposed in this paper. The paper provides an alternative current control approach to control the bias voltage compensation for full-color LED display based on the load-line approach. Modeling and formulation of the driver circuit system will be discussed in detail. Bias voltage compensation based on three load-lines regulation will keep the operating point fixed for the three color cells. Many properties can be observed based on the proposed model. Parasite effect such as the stray resistor and the stray capacitor will be considered in this paper. The associated standard RGB color testing for color cells and white color testing will be illustrated to verify the proposed compensation for the display driver circuit. The objectives of the luminance uniformity and the gray scale control can be achieved by using circuit approach. It is believed that this paper will be helpful to the driver circuit technology for the full-color LED display.

Let f and g be two maps from a set E into a set F such that f(x) g(x) for every x in E. Sahili [8] has shown that, if min {|f-1(z)|,|g-1(z)|}≤ n for each z∈ F, then E can be partitioned into at most 2n+1 sets E1,..., E2n+1 such that f(Ei)∩ g(Ei)= for each i=1,..., 2n+1. He also asked if 2n+1 is the best possible bound. By using Sahili's formulation of the problem in terms of the chromatic number of line digraphs, we improve the upper bound from 2n+1 to O(log n). We also investigate extended version for more than two maps.

In this paper, a chromatic adaptation model (CAM) based on the dependence on LMS cone responses of the human visual system (HVS) is proposed for TV and PC monitors under a variety of viewing conditions. We derived the proposed CAM based on Breneman's corresponding color data. The results of the experiments were carried out to assess the proposed model performance in terms of color fidelity by comparing complex images on a LCD monitor. We confirmed that the proposed model performed better to predict corresponding colors under various viewing conditions. Therefore, the reproduced colors, which are viewed in real surround viewing conditions, are perceived the same as original object colors, when the proposed CAM was applied to color display devices such as CRT, LCD, and PDP.

The path coloring problem is to assign the minimum number of colors to a given set P of directed paths on a given symmetric digraph D so that no two paths sharing an arc have the same color. The problem has applications to efficient assignment of wavelengths to communications on WDM optical networks. In this paper, we show that the path coloring problem is NP-hard even if the underlying graph of D is restricted to a binary caterpillar. Moreover, we give a polynomial time algorithm which constructs, given a binary caterpillar G and a set P of directed paths on the symmetric digraph associated with G, a path coloring of P with at most colors, where L is the maximum number of paths sharing an edge. Furthermore, we show that no local greedy path coloring algorithm on caterpillars in general uses less than colors.

Optical flow is usually computed only on the basis of intensity information of images. Therefore, if we use color information in addition to the intensity, it is expected that more accurate optical flow can be computed. However, this intuition will be correct only when the following conditions are satisfied. First, the images should contain rich color variations. Moreover, it is also required that the image gradient of each color band differs in its direction. In this report, we empirically examined the difference of gradient directions on each band using 500 images, and evaluated quantitatively the advantage of using color information for optical flow computation.

Since a human object is an important element of the moving pictures being processed by mobile terminals, establishing a human object extraction method encourages dissemination of new applications. In accordance with the requirement of mobile applications, this paper proposes a low-cost human object extraction method, which consists of a face object and a hair object extraction based on their color information and a simple body extraction utilizing the position information of the face object. In the proposed method, skin color and hair color are estimated through color space segmentation, and a human object is effectively extracted by using a radial active contour model. Simulation results of the human object extraction with the use of XScale processor claims that QCIF 15 fps video sequences can be processed in real time.

A novel approach for segmentation of grayscale images, which are color scene originally, is proposed. Many algorithms have been elaborated for a grayscale image segmentation. All those approaches have been discussed in a luminance space, because it has been considered that grayscale images do not have any color information. However, a luminance value has color information as a set of corresponding colors. In this paper, an inverse mapping of luminance values is carried out to CIELAB color space, and the image segmentation for grayscale images is performed based on a distance in the color space. The proposed scheme is applied to a region growing segmentation and the performance is verified.

We have developed new current demultiplexer TFT circuits for AMOLED and applied the circuits to 2.2-in. QVGA AMOLED. The combination of the current demultiplexer and our voltage boosted current programmed pixel can achieve good uniformity of display image and a compact module.

The RGB signals generated by different cameras are not equal for the same scene. Therefore, cameras are characterized based on a CIE standard colorimetric observer. One method of deriving a colorimetric characterization matrix between camera RGB output signals and CIE XYZ tristimulus values is least squares polynomial modeling. Yet, this involves tedious experiments to obtain a camera transfer matrix under various white balance points for the same camera. Accordingly, the current paper proposes a new method for obtaining camera transfer matrices under different white balances using a 33 camera transfer matrix under a specific white balance point.

Traffic sign recognition usually consists of two stages: detection and classification. In this paper, we describe the classification stage using the ring-partitioned method. The proposed method uses a specified grayscale image in the pre-processing step and ring-partitioned matching in the matching step. The method does not need carefully prepared many samples of traffic sign images for the training process, alternatively only the standard traffic signs are used as the reference images. The experimental results show the effectiveness of the method in the matching of occluded, rotated, and illumination problems of the traffic sign images with the fast computation time.

This paper presents a color demosaicing method by introducing iterative asymmetric average interpolation. Missing primary colors on a Bayer pattern color filter array (CFA) are estimated by an asymmetric average interpolation where less intensity variation is assumed to be of stronger significance, before sharpness of an initial estimate is further improved by an iterative procedure. The iteration is implemented by an observation process followed by a restoration process. The former is modeled by blurring followed by CFA sampling and the latter is completely as same as the color demosaicing method initially applied. Experimental results have shown a favorable performance in terms of PSNR and visual appearance, in particular, in sharpness recovery.

We have proposed in [5] a practical blind channel identification algorithm for the white observation noise. In this paper, we examine the effectiveness of the algorithm given in [5] for the colored observation noise. The proposed algorithm utilizes Gram-Schmidt orthogonalization procedure and estimates (1) the channel order, (2) the noise variance and then (3) the channel impulse response with less computational complexity compared to the conventional algorithms using eigenvalue decomposition. It can be shown through numerical examples that the algorithm proposed in [5] is quite effective in the colored noise case.

Screen pattern used in offset-printed documents has been one of great obstacles in developing document recognition systems that handle color documents. This paper proposes a selective smoothing method for filtering the screen patterns/noise in high-resolution color document images. Experimental results show that the method yields significant improvements in character pattern extraction.

In this paper, we propose a technique for detection and real-time tracking of moving targets. This uses a color segmentation algorithm robust to irregular illumination variation and a line-based tracker. The former is based on statistical representation of a color. And, we can obtain a real-time property for detection and tracking of moving targets from the latter.

A new edge-coloring algorithm for bipartite graphs is presented. This algorithm, based on the framework of the O(m log d + (m/d) log (m/d) log d) algorithm by Makino-Takabatake-Fujishige and the O(m log m) one by Alon, finds an optimal edge-coloring of a bipartite graph with m edges and maximum degree d in O(m log d + (m/d) log (m/d)) time. This algorithm does not require elaborate data structures, which the best known O(m log d) algorithm due to Cole-Ost-Schirra depends on.