Color Gamut Mapping Research Articles

Reconstructing the Colors of Underwater Images Based on the Color Mapping Strategy

Underwater imagery plays a vital role in ocean development and conservation efforts. However, underwater images often suffer from chromatic aberration and low contrast due to the attenuation and scattering of visible light in the complex medium of water. To address these issues, we propose an underwater image enhancement network called CM-Net, which utilizes color mapping techniques to remove noise and restore the natural brightness and colors of underwater images. Specifically, CM-Net consists of a three-step solution: adaptive color mapping (ACM), local enhancement (LE), and global generation (GG). Inspired by the principles of color gamut mapping, the ACM enhances the network’s adaptive response to regions with severe color attenuation. ACM enables the correction of the blue-green cast in underwater images by combining color constancy theory with the power of convolutional neural networks. To account for inconsistent attenuation in different channels and spatial regions, we designed a multi-head reinforcement module (MHR) in the LE step. The MHR enhances the network’s attention to channels and spatial regions with more pronounced attenuation, further improving contrast and saturation. Compared to the best candidate models on the EUVP and UIEB datasets, CM-Net improves PSNR by 18.1% and 6.5% and SSIM by 5.9% and 13.3%, respectively. At the same time, CIEDE2000 decreased by 25.6% and 1.3%.

Color gamut extension algorithm for various images based on laser display.

In pursuit of enhancing the display performance of gamut extension algorithms across diverse image types while minimizing image dependency, this study introduces a dynamic gamut extension algorithm. The algorithm is designed to extend the sRGB source gamut towards the wide gamut of a laser display. To evaluate its effectiveness, psychophysical experiments were conducted using four distinct image categories: complexions, scenery, objects, and color blocks and bars. The performance of the proposed algorithm was benchmarked against four established color gamut mapping algorithms. The comparative analysis revealed that our algorithm excels in handling wide color gamuts, outperforming the alternatives in terms of preference and the preservation of detail richness.

Spectral-level assessment of light pollution from urban façade lighting

Façade lighting makes cities brighter at night and causes ecological impacts, as more wavelengths associated with species spectral sensitivity are emitted in light spectra. To assess the resulting ground-level light pollution and explore ecological lighting strategies, this study collected hyperspectral data of 74 lighting facades in Shanghai, China and analyzed lighting features related to ecological impacts. Spectral-level assessment shows that multi-spectral lighting causes higher luminance, more variable colours, and stronger eco-impacts, e.g., on human circadian rhythms, human photopic vision and plant photosynthesis than uniform-colour lighting. High ecological impacts are associated with narrow spectra of saturated blue and red colours, and cannot be effectively reduced by luminance control. A colour gamut mapping strategy is thus proposed to reduce the eco-impacts through colour restriction. This study quantitatively assesses the light pollution from façade lighting and reveals the associations between different lighting indicators and ecological impacts. The colour gamut mapping strategy provides a trade-off between visual effects and eco-impacts, which helps to balance the needs of urban development and environment. The findings provide guidance to lighting manufacturers, designers and policy makers on eco-lighting design and its integration into sustainable lighting masterplans.

52‐5: A Color Gamut Mapping Method Using an OLED Display Model

In this paper, we introduce how to map the native Organic Light Emitting Diode (OLED) panel's color gamut to the standard gamut (i.e., sRGB or P3). In order to achieve better accuracy and speedy mapping for the overall gamut region, we modeled OLED panel considering IR‐drop and Lateral leakage which are unique properties of OLED. In the experiment results, it is confirmed that the native mobile OLED panel was tuned to the standard gamut properly and proposed Color Gamut Mapping (CGM) result had an average distortion less than 0.4 in CIEDE2000. (It almost equals to 0.5 JNCD) In addition, whole calibration procedure can be performed within 1 minute by using proposed method, so that could be applied to individual panel calibration in a factory line.

Improving picture‐reproducing quality by a new color gamut mapping method

AbstractThe color gamut of input source and the display set usually are disparate; therefore, a mapping mechanism between them is necessary and makes significant impact on the picture‐reproducing quality. In this paper, a new gamut mapping algorithm is proposed, which reduces color difference significantly between the source and target, compared with that without adopting such mapping process. The gamma behavior of luminance dependence on gray scale has been little affected. Artifacts like saturation inversion and hue inconsistency are avoided.

Expanding the color gamut of inkjet textile printing during color matching

AbstractOne of the most important subjects of digital printing is evaluation of color gamut mapping. A printer can only reproduce colors that are in its color gamut. Maybe, a color tolerance between reference sample and printed sample is in agreement between manufacturer and customer. The goal of this work is to estimate the expansion of the color gamut of an inkjet textile printer by consideration of the acceptable (predetermined) color difference during color matching. For analyzing the color gamut, a standard color chart IT8.7/4‐2005 CMYK target was printed by nine different mixtures of CMYK, and then the reflectance spectra and colorimetric parameters of the printed samples were measured. The inks used were disperse water‐based inks that were printed on the polyester fabric. The maximum acceptable color difference in this study was equal to 2 CIELAB units for all colors. In order to estimate the color gamut with the maximum acceptable color difference, for all boundary points of gamut, expanded points were obtained by Euclidean distance less than = 2. The results show that when the acceptable color difference is considered in color gamut measuring, the area and volume of the color gamut are increased and so, the reproducibility of printer is increased. The maximum and minimum expansions of color gamut volumes were obtained by the mixtures with minimum and maximum color gamuts, respectively. The volume expansion of the mixture with the minimum color gamut volume was 34.20%, while the volume expansion of the mixture with the maximum color gamut volume was 28.06%.

P‐7.1: A Methodology of Color Gamut Mapping with the Modification of Color Temperature

As the application of AMOLED becomes more and more popular, the technologies are needed to implement color management and gamut mapping. The paper proposes a mapping method to adjust the color gamut and color temperature. We add additional white color to achieve the control of color temperature when implementing gamut tuning flow. The original gamut is also separated into RGW/RWB/WGB and perform the multiply of 3x3 matrix to iterate its XYZ calculation respectively. In experiment result, the color ticks of specified gamut can fit its mismatch tolerance and implement desired gamut remapping.

2.4: Improving Picture‐reproducing Quality by a New Color Gamut Mapping Method

The color gamut of input source and the display set usually are disparate, therefore, a mapping mechanism between them is necessary and makes significant impact on the picture reproducing quality. In this paper, a new gamut mapping algorithm is proposed, which reduces color difference significantly between the source and target, compared with that without adopting such mapping process. The gamma behavior of luminance dependence on gray scale has been little affected. Artifacts like saturation inversion and hue inconsistency are avoided.

A testing paradigm for quantifying ICC profilers

To reproduce colors in one system which differs from another system in terms of the color gamut, it is necessary to use a color gamut mapping process. This color gamut mapping is a method to translate a specific color from a medium (screen, digital camera, scanner, digital file, etc) into another system having a difference in gamut volume. There are different rendering intent options defined by the International Color Consortium [5] to use the different reproduction goals of the user [19]. Any rendering intent used to reproduce colors, includes profile engine decisions to do it, i.e. looking for color accuracy, vivid colors or pleasing reproduction of images. Using the same decisions on different profile engines, the final visual output can look different (more than one Just Noticeable Difference[16]) depending on the profile engine used and the color algorithms that they implement. Profile performance substantially depends on the profiler engine used to create them. Different profilers provide the user with varying levels of liberty to design a profile for their color management needs and preference. The motivation of this study is to rank the performance of various market leading profiler engines on the basis of different metrics designed specifically to report the performance of particular aspects of these profiles. The study helped us take valuable decisions regarding profile performance without any visual assessment to decide on the best profiler engine.

P‐13.11: A Color Gamut Mapping Reducing the Influence of IR‐drop in OLED Displays

In this paper, a method of reducing the influence of IR‐drop in OLED display for color gamut mapping (CGM) is described. Due to the IR‐drop, the parameters can be hardly calculated only by formulas, which make the inaccuracy of CGM.This algorithm uses the IR‐drop data of specific gray scale data to find out the IR‐drop rule of arbitrary gray scale. The method is easy and accurate to reduce the influence of IR‐drop, making the CGM better applied to OLED displays.

Color gamut mapping between small and large color gamuts: part II. gamut extension.

A wide color gamut (WCG) display has great color rendering capability and offers the opportunity to achieve a pleasing and realistic appearance in terms of image quality. To take full advantage of the large display gamut, a new gamut extension algorithm (GEA) is proposed based on a new color appearance scale, vividness. The performance of the new GEA was investigated via a psychophysical experiment together with five commonly used GEAs. In addition, two different uniform color spaces (UCSs) were also studied including the CAM02-UCS color space and a space, Jzazbz, designed for high dynamic range (HDR) and WCG applications. The results showed that the newly proposed GEA, i.e. the vividness-extension (VE) algorithm, outperformed all the other GEAs and the Jzazbz space was a promising UCS for evaluating gamut extension.

Colour gamut mapping between small and large colour gamuts: Part I. gamut compression.

This paper describes an investigation into the performance of different gamut compression algorithms (GCAs) in different uniform colour spaces (UCSs) between small and large colour gamuts. Gamut mapping is a key component in a colour management system and has drawn much attention in the last two decades. Two new GCAs, i.e. vividness-preserved (VP) and depth-preserved (DP), based on the concepts of 'vividness' and 'depth' are proposed and compared with the other commonly used GCAs with the exception of spatial GCAs since the goal of this study was to develop an algorithm that could be implemented in real time for mobile phone applications. In addition, UCSs including CIELAB, CAM02-UCS, and a newly developed UCS, Jzazbz, were tested to verify how they affect the performance of the GCAs. A psychophysical experiment was conducted and the results showed that one of the newly proposed GCAs, VP, gave the best performance among different GCAs and the Jzazbz is a promising UCS for gamut mapping.

Color CLU-DBS Halftoning based on Neugebauer Primary Area Coverage: Improving the Breed

Though a color aperiodic, clustered-dot, halftoning (NPACMS-MP-CLU-DBS) algorithm can overcome the visible moire and rosette artifacts in conventional color halftoning methods, it still has some disadvantages, such as the color mismatch caused by the initial stage color management method, and texture artifacts caused by the concentric-ring cluster structure. In this paper, first, a new color gamut mapping method is used during the color management process, that is an image-dependent mapping method, which can make the most use of the printer color gamut, in order to reduce the color mismatch between the continuous-tone original and printed halftone images. Secondly, a new color, clustered-DBS halftoning algorithm with separated-cluster structure is developed. As a color halftoning method based on the clustered-DBS algorithm, not only it can overcome the visible moire and rosette artifacts, but also the separated-cluster structure is more stable, compared with the concentric-ring cluster structure. It can also reduce the texture artifacts significantly.

RGBW子像素排列结构改进与色域映射优化算法

RGBW子像素排列结构改进与色域映射优化算法

3D Visualization of out-of-gamut in Graphic Communication

In order to achieve high-fidelity representation of colors, it needs to do some purposeful interference when colors are conversed, so the color gamut mapping which is the main technology to ensure visual matching would be used during this process. And the accurate visualization of out-of-gamut between images and devices plays an important role in color gamut mapping, so a method of the 3D visualization of out-of-gamut in graphic communication based on segment maxima algorithm was proposed in this paper. And this method mainly had two steps, the first step was that the device color gamut boundary points could be obtained when used the color conversed information in digital output device profile, so as to generate accurate device color gamut. The next step was that out-of-gamut points could be obtained through making comparison between device gamut and digital image gamut, as result that the area of out-of-gamut could be presented in digital images and image gamut according to the out-of-gamut cloud dots. The advantages of this method were that it can encourage us to predict whether the image gamut is beyond the output device gamut in advance, and then it can help us to select appropriate color gamut mapping algorithm according to the result of out-of-gamut judgment, so as to realize the accurate reproduction of colors.

A new image spatial color gamut mapping algorithm

A new image spatial color gamut mapping algorithm

Development of XYZ/sRGB-SCID and Color Gamut Mapping

Development of XYZ/sRGB-SCID and Color Gamut Mapping

A new out-of-gamut determination method of image based on irregular segmentation

The out-of-gamut determination of images is very important for color gamut mapping which plays an important role in cross-media color reproduction. In this paper, aiming to achieve an accurate out-of-gamut determination of image and exploit the full potential of the reproduction device gamut, we propose a out-of-gamut determination method of images based on irregular segmentation which divides the color gamut into several parts according to the chroma and lightness of colors in CIELAB color space. First, the device color gamut is divided into the high-chroma and the low-chroma color parts, and the high-chroma parts are divided into more segments through the CIELAB a*b* plane when calculating color gamut descriptors. Then, in each segment the radiuses between the color points and the center point are calculated. For the color points located in the high-chroma parts, the color point with the biggest radius is selected as the gamut boundary descriptor, and for that in the low-chroma parts, if the corresponding outer segments are empty, the color point with the biggest radius is selected as the gamut boundary descriptor. Through the irregular segmentation of gamut, the GBDs distribute more uniformly among the color gamut surface than segment maximum method which treats all colors in the same way wherever they are located in the gamut. After that, determination of the out-of-gamut colors can be done by calculating the position relationship between the source colors and the GBDs. Additionally, GMAs would benefit from this accurate out-of-gamut determination of image. GMAs based on this out-of-gamut determination method validate the promising results.

Cross‐media colour gamut mapping model for the preservation of visual differentials in layer‐tinted maps

Aiming at solving the colour union, variation and loss problems during cross-media reproduction in the layer-tinted map, this study proposes a colour gamut mapping model for the preservation of visual differentials in layer-tinted maps. First, many layer-tinted maps are collected for analysis and the colouring rules are concluded. Then, the dominant and non-dominant colours are extracted based on the colour gamut characteristics of the maps. For the mapping of dominant colours, the corresponding Munsell's three colour dimensions are calculated by establishing the transformational relation between CIELAB colour space and Munsell's colour system and then the colour gamut mapping of dominant colours is achieved in the Munsell's colour order system. On the other hand, the mapping of non-dominant colours is achieved by hue-angle preserving minimum ΔE clipping. The experimental results indicate that compared with the four colour gamut mapping methods recommended by the International Color Consortium, the proposed algorithm in this study can more easily distinguish the hierarchical information in the maps and perfectly remain the visual differentials among the layered colours.

A new device color gamut boundary description algorithm based on irregular segmentation

AbstractThe description of device color gamut is very important for color gamut mapping, which plays an important role in cross‐media color reproduction. To get a more accurate color gamut boundary, several gamut boundary description (GBD) methods have been presented in the past; however, many problems still exist in the current algorithm (e.g., accuracy and speed). In this study, we propose a new device GBD method based on irregular segmentation and evaluate it against other GBD algorithms. In the irregular segmentation method, the device color gamut is divided into the high‐chroma and the low‐chroma color parts, and the high‐chroma parts are divided into more segments through the CIELAB a*b* plane when calculating color gamut descriptors. After that, in each segment, the radii between the color points and the center point are calculated. For the color points located in the high‐chroma parts, the color point with the biggest radius is selected as the gamut boundary descriptor, and for that in the low‐chroma parts, if the corresponding outer segments are empty, the color point with the biggest radius is selected as the gamut boundary descriptor. Then, the gamut boundary descriptors are visualized in CIELAB color space using triangulation method. Finally, the irregular segmentation method is evaluated in contrast with other GBD methods using gamut mismatch index. The results show that the irregular segmentation method performs better in accuracy and has smaller variance. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 173–181, 2017