Wide color gamut media are emerging in the market, and this trend has been accelerated by ITU recommendation, Rec.2020 in 2012. Wide color gamut media possess spectrally narrow primaries, which would potentially increase the degree of observer metamerism. In this study, it was investigated if observer metamerism could be a serious issue under practical viewing conditions. Namely, real images were used as a matching stimulus instead of uniform colors. We carried out the color image matching experiment on two different media: an Apple Cinema HD LCD monitor and a Microvision laser projector. The results from 28 color-normal observers were analyzed. The obtained inter-observer variability was large enough that observer metamerism would be a serious issue where the laser projector is viewed together with conventional media. Each observer had a match point that was significantly different from those of other observers. It was found that effective field size changes (and an observers CMFs change) depending on image contents. Complex images require smaller field size whereas simple images require larger field size.

The perceptual gloss space defined in Pellacini et al. [9] could be used for quality control applications to bring similar benefits as seen in color with the use of CIELAB. However, a distance metric to relate all the dimensions in the space does not exist, and the space was only validated with the materials used to define the space. The current space's distance metric does not allow relating differences in lightness to the other dimensions: contrast gloss and distinctness of image gloss. The lightness perception uniformity of the space was first evaluated in a psychophysical study, where the observers' lightness discrimination was found to decrease as lightness increased. A function was derived to model the lightness perception observed and it was included into the distance metric of the space. The space uniformity around sixteen positions in the gloss space was evaluated in a second psychophysical study to assess the overall space uniformity. The space was found to be perceptually non-uniform outside the samples used when the space was created. Also, an improved gloss difference equation that takes into account the non-uniformity of the space is presented, showing a statistical significant improvement over the current gloss difference equation of the space and reducing the STRESS value from 39.76 to 22.96.

The electronic display industry has begun a migration towards higher color gamut devices driven by LED, OLED, quantum dot and laser technologies capable of generating near monochromatic color stimuli in the traditional red, green, blue three-channel paradigm. The use of highly selective spectral stimuli, however, poses a risk to the consistency of visual experience amongst a group of disparate, but otherwise normal, color observers. Several models of spectral color vision have surfaced in recent research and are helping investigators to better understand the implications for color experience variability. The present research serves to summarize various color difference indices that may be useful in predicting the magnitude of observer response inconsistencies and applies them to simulations of current electronic displays as examples of potential concerns these new high-gamut technologies might raise. In particular, various laser-based displays are shown to perform with significantly increased observer variability versus traditional ITU-R Rec. 709 and SMPTE 431 RGB-primary displays utilized in the cinema industry. Further, observer metamerism can be reduced significantly with proper optimization of a multichannel projection system comprising seven explicitly designed primary spectra. © 2014 Society for Imaging Science and Technology. [DOI:10.2352/J.ImagingSci.Technol.2014.58.3.030402]

The authors propose a method of image rendering to predict the incomplete chromatic-adaptation effect for paintings. A simple model of incomplete chromatic adaptation is developed to predict the appearance of the paintings under the illumination of an incandescent light source and to produce the full color image on a display device. The authors extend the von Kries framework to incomplete chromatic adaptation. An index parameter representing the degree of incomplete chromatic adaptation is defined based on the color temperature of the black-body radiators. First, the optimum value of the index parameter is determined by visual experiments on memory matching using real paintings and color patches, so that the color image produced on the display is matched to the original appearance of objects in a real scene. This approach is shown to have better performance in comparison with the traditional CIECAM02. Next, an algorithm is presented to estimate the index parameter of the incomplete adaptation index based on the image data of colorimetric rendering for a target painting. It is found that the index parameter can be estimated using only three features extracted from the color image. The color images rendered with the estimated parameter are used to predict the incomplete chromatic-adaptation effect for the original painting under the incandescent light source. The feasibility of the proposed method is confirmed based on a series of experiments using a variety of paintings. © 2014 Society for Imaging Science and Technology. [DOI:10.2352/J.ImagingSci.Technol.2014.58.3.030403]

Many image quality and image difference metrics have been proposed over the last decades. An important factor when evaluating the image quality or image difference is the viewing distance. In this paper we propose a new image difference metric based on the simulation of detail visibility and total variation. The simulation of detail visibility by using shearlets takes into account the viewing conditions and the viewing distance, and calculation of the image difference is done by total variation. Evaluation has been carried out to verify the simulation of image detail visibility, and it is showing promising results. Evaluation of the new image difference metric is also promising.

Gamut reduction transforms the colors of an input image within the range of a target device. A good gamut reduction algorithm will preserve the experience felt by the viewer of the original image. Saliency algorithms predict the image regions where an observer first focuses. Therefore, there exists a connection between both concepts since modifying the saliency of the image will modify the viewer's experience. However, very little attention has been given to relate saliency and gamut mapping. In this paper we propose to modify a recent gamut reduction algorithm proposed by Zamir et al. [33] in order to better respect the saliency of the original image in the reproduced one. Our results show that the proposed approach presents a gamut-mapped image whose saliency map is closer to that of the original image with a minor loss in the accuracy of perceptual reproduction.

Advanced printing techniques are currently used to incorporate special effects in printouts. There is an increasing interest in the reproduction of material appearances and art work, with the focus on reproducing aspects such as colour, surface texture and gloss variations. However, for material surfaces of which the level of glossiness varies, the colour is often affected due to the applied gloss effect. The effect of the (local) gloss level on the colour is not incorporated in the colour management, which results in a mismatch with respect to the intended colour. We propose a workflow to control the reproduction of colour for the case of using multiple gloss modes in a printing system. Although currently one single ICC profile is used to manage the colour of the printout, our workflow proposes using one ICC profile per gloss level that adapts the colour transformations locally based on the applied gloss level. Our results show an improved reproduction of the colour and smoother colour transitions between gloss levels of prints with variant gloss.

Denoising algorithms are usually tested on standard test images with artificial white Gaussian noise added. This noise model cannot be applied in the denoising of digital images taken with a single sensor camera because of the signal-dependence of the noise, the demosaicking and the color transformations. We study the noise characteristics with respect to the signal domain. Noise distribution and variance are measured in the raw data and approximated using a Gaussian distribution with a variance linearly dependent on the signal. We evaluate the influence of white balance, debayering and the signal domain and calculate the spatial correlation of the noise. In our experiments we both evaluate the influence of the noise characteristics on human perception and on the performance of denoising methods. Based on a subjective test with 18 participants we can show that the spatially correlated camera noise is more visible than the white Gaussian noise and decreases the visual quality of color image sequences significantly. To evaluate the impact of the noise characteristic on denoising, two state-of-the-art denoising methods are applied to our test data. When the noise is signal-dependent and spatially correlated through debayering the peak signal-to-noise ratio (PSNR) decreases by up to 8 dB. We conclude that it is very important to take into account the correct noise characteristics for increasing the visual quality of color image sequences in future research.

Atmospheric pollution by PM2.5 is a serious problem now at Beijing, China and its neighboring countries. The de-hazing or de-fogging methods for degraded images have been a long-pending question at NASA Langley Research Center. Recently their basic Retinex model advanced into Visual Servo system. While the current main stream for unveiling the atmospheric pollution layer is based on scattering physics. Above all, a single image de-hazing model based on Dark Channel Prior hypothesis is most notable in practice. The keys to unveiling the pollution layer lie in the two points: [1] how to extract the skylight and [2] how to estimate the scene transmittance. This paper proposes a simple but effective de-hazing algorithm with banding-free and low computation costs referring to the Dark Channel Prior hypothesis. The simulation shows how the proposed model works to look the scene through heavy air pollution.

Oppopnent-color mechanism in the retinal ganglion cell carries the luminance-chrominance transform important to human vision. Though a variety of opponent-color spaces have been proposed, the orthonormality and the achromatic grayness in the basis function are not always guaranteed. This paper discusses a foundation of complete opponent-color space based on the concept of FCS (Fundamental Color Space) derived from Matrix-R theory. A complete opponent-color space is constructed by [1] choosing the Golden Vectors as an orthogonal triplet for FCS, [2] replacing its luminance basis by the fundamental of EE spectrum, and [3] orthonormalizing the basis functions with GramSchmidt method. The fundamental of EE spectrum is bimodal-shaped. This distinct basis makes the mathematical completeness in the opponent-color FCS possible. So far, the Golden Vectors with fundamentals for (λ₁=455, λ₂ =513, λ₃=584 nm) by J. B Cohen is known to give an ideal orthogonal triplet, but is not an optimal set. The author found a new set of Golden Vectors with the fundamentals for (λ₁=461, λ₂=548, λ₃=617 nm) as the best. A complete opponent-color FCS satisfying both orthonormality and chromatic graynesss is derived from this new Golden Vectors. The paper shows how the proposed opponent-color FCS works well to separate the opponent-color components for natural images and introduces an application to the image color segmentation.