When collecting images, owing to the influence of shooting equipment, shooting environment, and other factors, often low-illumination images with insufficient exposure are obtained. For low-illumination images, it is necessary to improve the contrast. In this paper, a digital color image contrast enhancement method based on luminance weight adjustment is proposed. This method improves the contrast of the image and maintains the detail and nature of the image. In the proposed method, the illumination of the histogram equalization image and the adaptive gamma correction with weighted distribution image are adjusted by the luminance weight of w1 to obtain a detailed image of the bright areas. Thereafter, the suppressed multi-scale retinex (MSR) is used to process the input image and obtain a detailed image of the dark areas. Finally, the luminance weight w2 is used to adjust the illumination component of the detailed images of the bright and dark areas, respectively, to obtain the output image. The experimental results show that the proposed method can enhance the details of the input image and avoid excessive enhancement of contrast, which maintains the naturalness of the input image well. Furthermore, we used the discrete entropy and lightness order error function to perform a numerical evaluation to verify the effectiveness of the proposed method.

Recently, visual trackers based on the framework of kernelized correlation filter (KCF) achieve the robustness and accuracy results. These trackers need to learn information on the object from each frame, thus the state change of the object affects the tracking performances. In order to deal with the state change, we propose a novel KCF tracker using the filter response map, namely a confidence map, and adaptive model. This method firstly takes a skipped scale pool method which utilizes variable window size at every two frames. Secondly, the location of the object is estimated using the combination of the filter response and the similarity of the luminance histogram at multiple points in the confidence map. Moreover, we use the re-detection of the multiple peaks of the confidence map to prevent the target drift and reduce the influence of illumination. Thirdly, the learning rate to obtain the model of the object is adjusted, using the filter response and the similarity of the luminance histogram, considering the state of the object. Experimentally, the proposed tracker (CFCA) achieves outstanding performance for the challenging benchmark sequence (OTB2013 and OTB2015).

In recent years, flexible liquid crystal displays (LCDs) have attracted much attention due to their thin and lightweight designs, as well as their ease of installation compared with conventional flat-panel LCDs. Most LCDs require backlight units (BLUs) to yield high-quality images. However, the luminance uniformity of flexible BLUs is drastically reduced in the curved state, as the light emitted from a typical BLU is mainly directed in the normal direction. Conventional BLUs do not provide the image quality of flexible BLUs due to uneven luminance distribution from the perspective of the observer. To overcome these issues, here we introduce a novel oblique-angled notched film for improved light distribution of a conventional BLU. The notched structure of the proposed film exhibits V-shaped split behavior during curvature. This elastic deformation is expected to compensate for the spatial luminance of the light emitted from the BLU. We investigated the design requirements for the proposed film based on geometrical calculations. The luminance distribution of a flexible BLU was then simulated using the proposed film, based on geometrical optics theory. The simulation results confirmed that the direction of travel of the light is controllable according to the total internal reflection of the proposed film, thus improving the luminance uniformity of the BLU in a convex-curved state. Based on these results, the proposed approach is expected to improve the luminance uniformity of convex-curved flexible LCDs.

We studied the detection of the incongruence between the two eyes' retinal images from occlusion perception. We previously analyzed the evasion action caused by occlusion by using green-red equiluminance, which is processed by parvocellular cells. Here we analyzed this action by using yellow-blue equiluminance, which is said to be treated by koniocellular cells and parvocellular cells. We observed that there were the cases in which the subject could perceive incongruence by the occlusion and other cases in which the subject could not perceive it. Significant differences were not seen in all conditions. Because a difference was seen in an evasion action at the time of the rim occlusion gaze when we compare the result for the yellow-blue equiluminance with the green-red equiluminance, it is suggested that the response for each equiluminance is different. We were able to clarify the characteristic difference between parvocellular cells and koniocellular cells from an occlusion experiment.

Stereoscopic vision technology is applied in a wide range of fields, from 3D movies to medical care. Stereoscopic vision makes it possible to observe images in parallax between both eyes. However, parallax images cannot be used all the time due to a situation called “occlusion”, in which an object is hidden in the depths by another object. In this case, different images are projected on the right and left retina. Here, we propose a psychology experiment to elucidate the function of parvocellular cells in the LGN of the visual cortex of the brain using occlusion perception. As a new psychology experiment to clarify whether parvocellular cells in the LGN of the visual cortex, said to process chromatic and luminance information, can detect a disagreement between the retinal images produced by each eye, we measured convergence eye movement when gazing at the rim of a column under occlusion using an equiluminance random dot pattern. When eye movement prevented the disagreement of the retinal images caused by occlusion, we thought that convergence eye movement to move both eyes in front of the rim or divergence eye movement to move them behind the rim would occur. In other words, we thought that we could clarify whether there was parvocellular system process agreement or disagreement between the right and left retinal images under equiluminance. Therefore, we examined whether a system to detect disagreement between the retinal images exists in the brain when gazing at the rim of a column onto which an equiluminance random dot texture was mapped. Results suggested that the mechanism to avoid disagreement between the retinal images of the eyes caused by occlusion occurs in the parvocellular cells, which mainly process color information, as well as in the magnocellular cells, which process binocular disparity.

Previously, it is not obvious to what extent was accepted for the assessors when we see the 3D image (including multi-view 3D) which the luminance change may affect the stereoscopic effect and assessment generally. We think that we can conduct a general evaluation, along with a subjective evaluation, of the luminance component using both the S-CIELAB color space and CIEDE2000. In this study, first, we performed three types of subjective evaluation experiments for contrast enhancement in an image by using the eight viewpoints parallax barrier method. Next, we analyzed the results statistically by using a support vector machine (SVM). Further, we objectively evaluated the luminance value measurement by using CIEDE2000 in the S-CIELAB color space. Then, we checked whether the objective evaluation value was related to the subjective evaluation value. From results, we were able to see the characteristic relationship between subjective assessment and objective assessment.

A method of color scheme is proposed considering contrast of luminance between adjacent regions and design property. This method aims at setting the contrast of luminance high, in order to make the image understandable to visually handicapped people. This method also realizes preferable color design for visually normal people by assigning color components from color combination samples. Interactive evolutionary computing is adopted to design the luminance and the color, so that the luminance and color components are assigned to each region appropriately on the basis of human subjective criteria. Here, the luminance is designed first, and then color components are assigned, keeping the luminance unchanged. Since samples of fine color combinations are applied, the obtained color design is also fine and harmonic. Computer simulations verify the high performance of this system.

We investigated effects of ultraviolet illuminance and ratio of high- to low-refractive-index monomers on the layer structure and light diffusion properties of light-diffusing films with alternating polymer layer structures. We clarified that an increasing difference in refractive index between alternating polymer layers induced an increase in the diffusion angle.

We estimated the dependence of the perceived depth on luminance ratio by increasing the distance between the front and rear planes of a depth-fused 3-D (DFD) display. When the distance is great, the perceived depth has the tendency of nonlinear dependence on luminance ratio, which is very different from the almost linear dependence in a short-distance conventional DFD display. In a long-distance DFD display, the perceived depth is split to near the front plane at 0-40% of the rear luminance, near the rear plane at 70-100%, and the midpoint of the front and rear planes at 40-60%. Thus, the luminance-ratio dependence of perceived depth changes widely with the distance.

We developed a quantitative evaluation method for luminance and color uniformity on a display screen. In this paper, we report the analysis result of a viewer perception of luminance and color uniformity. In experiments, observers subjectively evaluated Mura images which were showed on the light emitting diode (LED) backlight screen by adjusting the luminance of each LED. We measured the luminance and color distributions of the Mura images by a 2D colorimeter, then, the measured data was converted into S-CIELAB. In S-CIELAB calculations, two dimensional MTF (Modulation Transfer Function) of human eye were used in which anisotropic properties of the spatial frequency response of human vision were considered. Some indexes for a quantitative evaluation model were extracted by the image processing. The significant indexes were determined by the multiple regression analysis to quantify the degree of uniformity of the backlight screen. The luminance uniformity evaluation model and color uniformity evaluation model were derived from this analysis independently. In addition, by integrating both of these models we derived a quantitative evaluation model for luminance and color unevenness simultaneously existing on the screen.

Recently, a novel approach to color image compression based on colorization has been presented. The conventional method for colorization-based image coding tends to lose the local oscillation of chrominance components that the original images had. A large number of color assignments is required to restore these oscillations. On the other hand, previous studies suggest that an oscillation of a chrominance component correlates with the oscillation of a corresponding luminance component. In this paper, we propose a new colorization-based image coding method that utilizes the local correlation between texture components of luminance and chrominance. These texture components are obtained by a total variation regularized energy minimization method. The local correlation relationships are approximated by linear functions, and their coefficients are extracted by an optimization method. This key idea enables us to represent the oscillations of chrominance components by using only a few pieces of information. Experimental results showed that our method can restore the local oscillation and code images more efficiently than the conventional method, JPEG, or JPEG2000 at a high compression rate.

This report describes a quantification method for luminance non-uniformity of a large LED backlight. In experiments described herein, participants subjectively evaluated artificial indistinct Mura images that simulated luminance non-uniformity of an LED backlight. We measured the luminance distribution of the Mura images. Then, the measured luminance distribution was converted into S-CIELAB, in which anisotropic properties of the spatial frequency response of human vision were considered. Subsequently, some indexes for the quantification model were extracted. We conducted multiple regression analyses using the subjective evaluation value and the index values obtained from measured luminance of Mura image. We proposed a quantification model consisting of four indexes: high and low luminance area, number of Mura edges, sum of Mura edge areas, and maximum luminance difference.

Minimizing the residual impurity gases is a key factor for reducing temporal dark image sticking. Therefore, this paper uses a vacuum-sealing method that minimizes the residual impurity gases by enhancing the base vacuum level, and the resultant change in temporal dark image sticking is then examined in comparison to that with the conventional sealing method using 42-in. ac-PDPs with a high Xe (11%) content. As a result of monitoring the difference in the display luminance, infrared emission, and perceived luminance between the cells with and without temporal dark image sticking, the vacuum-sealing method is demonstrated to reduce temporal dark image sticking by decreasing the residual impurity gases and increasing the oxygen vacancy in the MgO layer. Furthermore, the use of a modified driving waveform along with the vacuum-sealing method is even more effective in reducing temporal dark image sticking.

A novel driving concept, "pulse-width modulation with current uniformization," is proposed for thin-film transistor driven organic light-emitting diode displays (TFT-OLEDs). An example of this driving concept is the combination of "pulse-width modulation with a self-biased inverter" and a "time-ratio grayscale with current uniformization." Its driving operation is confirmed by circuit simulation. It is found that this driving method can compensate the characteristic deviations and degradations of both TFTs and OLEDs and immensely improve luminance uniformity. Finally, its driving operation is also confirmed by an actual pixel equivalent circuit.

An analytical approach using human perception has been applied to the evaluation of the front-of-screen (FOS) quality of liquid crystal displays (LCDs), particularly regarding the regions of luminance nonuniformity called "muras." The accurate and consistent inspection of muras is extremely difficult because muras have various shapes and sizes as well as contrasts. And inspection results tend to depend on inspectors during the LCD manufacturing process. To determine the quantitative scale that shows the evaluation results of mura matching human perceptions, first, we conducted a perception test and clarified the "just noticeable difference" (JND) contrast according to the type of mura. Second, the relationship between the JND contrast of mura and background luminance was investigated. Finally, we proposed a quantitative scale of mura level on the basis of the JND contrasts at various background luminances. In this paper, we describe our research on human perception of muras at various background luminances and an approach to determining the quantitative scale of visible muras.

We investigated physical conditions for optimum display systems on various TV viewing conditions, and found that visual brightness function could be derived from relationships between Steven's power law and Bartleson-Breneman's brightness function, and that the optimum physical contrast ratio and compensated gamma for display system with adaptation luminance level could be obtained from the proposed brightness function.

We clarify the effective range of distance between the front and rear images of the depth-fused 3-D (DFD) visual illusion. The DFD visual illusion is perceived when two images with many edges in the front and rear frontal-parallel planes at different depths are overlapped from the viewpoint of an observer. We evaluated how the fusion of the DFD visual illusion depended on the difference in distance between the front and rear images when the distance between the two images was changed. Subjective tests clarified the cases where DFD can be applied.

A new dual-slope ramp (DSR) reset waveform is proposed to improve the dark room contrast ratio in AC-PDPs. The proposed reset waveform has two different voltage slopes during a ramp-up period. The first voltage slope lower than the conventional ramp voltage slope plays a role in producing the priming particles under the low background luminance, which is considered to be a kind of pre-reset discharge. On the other hand, the second voltage slope higher than the conventional ramp voltage slope produces a stable reset discharge due to the presence of the priming particles, but gives rise to a slight increase in the background luminance. Thus, a bias voltage is also applied during a part of the second voltage-slope period to adjust the background luminance and address discharge characteristics. As a result, the proposed dual-slope reset waveform can lower the background luminance without causing the discharge instability, thereby improving the high dark room contrast ratio of an AC-PDP without reducing the address voltage margin.

We present a novel adaptive method to improve the binarization quality of degraded word color images. The objective of this work is to solve a nonlinear problem concerning the binarization quality, that is, to achieve edge enhancement and noise reduction in images. The digitized data used in this work were extracted automatically from real world photos. The motion of objects with reference to static camera and bad environmental conditions provoked serious quality problems on those images. Conventional methods, such as the nonlinear adaptive filter method proposed by Mo, or Otsu's method cannot produce satisfactory binarization results for those types of degraded images. Among other problems, we note mainly that contrast (between shapes and backgrounds) varies greatly within every degraded image due to non-uniform illumination. The proposed method is based on the automatic extraction of background information, such as luminance distribution to adaptively control the intensity levels, that is, without the need for any manual fine-tuning of parameters. Consequently, the new method can avoid noise or inappropriate shapes in the output binary images. Otsu's method is also applied to automatic threshold selection for classifying the pixels into background and shape pixels. To demonstrate the efficiency and the feasibility of the new adaptive method, we present results obtained by the binarization system. The results were satisfactory as we expected, and we have concluded that they can be used successfully as data in further processing such as segmentation or extraction of characters. Furthermore, the method helps to increase the eventual efficiency of a recognition system for poor-quality word images, such as number plate photos with non-uniform illumination and low contrast.

We investigated the intercalation of water into BaMgAl10O17:Eu2+ (BAM), a blue phosphor that is used in plasma display panels. The adsorption and desorption characteristics of water with BAM have hysteresis; showing that water is intercalated into BAM. Using thermal analysis techniques, we suggested that water hydrated to barium ions caused oxidation. We found that the water intercalated into BAM played an important role in the oxidation of Eu2+ between 450 and 600, and contributed to a 10% degradation of luminance. In contrast, oxidation due to oxygen is a principal factor in degradation above 600 through baking process in air.