Natural Color Appearance Research Articles

Image tone mapping based on clustering and human visual system models

Natural scenes generally have very high dynamic range (HDR) which cannot be captured in the standard dynamic range (SDR) images. HDR imaging techniques can be used to capture these details in both dark and bright regions, and the resultant HDR images can be tone mapped to reproduce them on SDR displays. To adapt to different applications, the tone mapping operator (TMO) should be able to achieve high performance for diverse HDR scenes. In this paper, we present a clustering-based TMO by embedding human visual system models that function effectively in different scenes. A hierarchical scheme is applied for clustering to reduce the computational complexity. We also propose a detail preservation method by superimposing the details of original HDR images to enhance local contrasts, and a color preservation method by limiting the adaptive saturation parameter to control the color saturation attenuating. The effectiveness of our method is assessed by comparing with state-of-the-art TMOs quantitatively on large-scale HDR datasets and qualitatively with a group of subjects. Experimental results of both objective and subjective evaluations show that the proposed method achieves improvements over the competing methods in generating high quality tone-mapped images with good contrast and natural color appearance for diverse HDR scenes.

Color enhancement algorithm based on Daltonization and image fusion for improving the color visibility to color vision deficiencies and normal trichromats

In recent years, helping individuals with color vision deficiency to distinguish confusing colors in digital images, which is called Daltonization, is a hot topic. However, a number of Daltonization methods have a color reduction problem that causes unnatural image colors for normal color vision observers and those with anomalous trichromatic color vision deficiencies. A color-enhancing algorithm is proposed to make up for the shortage in color naturalness. Based on the conclusion in previous studies that colors confused in the same type of color blindness are approximately straight lines (called confusion lines) on the u ′ v ′ chromaticity plane and all of the confusion lines intersect at the same point (called the confusion point), we propose a polar coordinate transformation based on intersection points of confusion lines, which can transform chromaticity information into perceptually sensitive and perceptually insensitive color blindness information. From the two color-blind sensitive information of the Daltonized image and the one color-blind insensitive information of the original image, the three-dimensional information can be combined to obtain an enhanced image. The enhanced image has a similar color appearance of the Daltonized image under the perspective of dichromats and has a more natural and colorful color appearance under the perspective of anomalous and normal trichromats. In addition, we propose a lightness modification to reduce lightness errors between the enhanced images and the Daltonized images. The quantitative evaluation shows that the method proposed is effective but sacrificing a small amount of color contrast of the Daltonized images.

Experimental trait mismatches uncover specificity of evolutionary links between multiple signaling traits and their interactions in hummingbirds.

Many animal signals co-occur, and these signals may coevolve due to their interactive properties. Previous work has demonstrated ecological drivers of evolutionary relationships between signals and the environment, which leads to questions about why specific signal pairs evolved among species that possess multiple signals. We asked whether the coloration of different species was optimized for presentation with its natural behavioral display. We investigated this in "bee" hummingbirds, where males exhibit angle-dependent structurally-colored plumage and a stereotyped courtship (shuttle) display, by experimentally creating mismatches between the behavior and plumage of five species and quantifying how these mismatches influenced male color appearance during a display. Specifically, we photographed the plumage from a given species as we moved its feathers through the position-and-orientation-specific courtship display path of other species and quantified the resulting color appearance during the display in order to compare the mismatched color appearance to each species' natural color appearance. We found that mismatches significantly altered display flashiness (% change in coloration during displays) compared to the natural plumage-behavior pairings, and that such departures in flashiness were predicted by differences in shuttle behaviors alone. These results illustrate a tight evolutionary relationship between shuttle displays and color flashiness in these hummingbirds. Further, we found that interspecific variation in male plumage, behavior, and natural color appearance predicted deviations between natural and mismatched flashy color appearance. Altogether, our work provides a new method for testing signal coevolution and highlights the complex evolutionary relationships between multiple signals and their interactions.

Fusion of Color Images Based on Fuzzy Transform and Spatial Frequency

Multiple images of a scene, captured using different imaging devices and containing complementary information, are required to be combined into a single fused image. The fused image, so obtained, should ideally contain all important features of individual input images. Further, color image processing is also gaining importance in most of the real-life applications. Color images provide better visual information and are highly suitable for human visual perception. Motivated by the gaining importance of color image processing, fusion of color images is proposed. The fusion algorithm is proposed in HSV color space where the luminance components of multiple input images, based on fuzzy transform and spatial frequency, are fused. The chrominance information of input images provides color to the fused image. The fused image contains all important information and possesses natural color appearance. Experiments performed on various pairs of visible–infrared and multifocus images demonstrate the superiority of the proposed algorithm over recent state-of-the-art image fusion algorithms.

Improved Color Mapping Methods for Multiband Nighttime Image Fusion

Previously, we presented two color mapping methods for the application of daytime colors to fused nighttime (e.g., intensified and longwave infrared or thermal (LWIR)) imagery. These mappings not only impart a natural daylight color appearance to multiband nighttime images but also enhance their contrast and the visibility of otherwise obscured details. As a result, it has been shown that these colorizing methods lead to an increased ease of interpretation, better discrimination and identification of materials, faster reaction times and ultimately improved situational awareness. A crucial step in the proposed coloring process is the choice of a suitable color mapping scheme. When both daytime color images and multiband sensor images of the same scene are available, the color mapping can be derived from matching image samples (i.e., by relating color values to sensor output signal intensities in a sample-based approach). When no exact matching reference images are available, the color transformation can be derived from the first-order statistical properties of the reference image and the multiband sensor image. In the current study, we investigated new color fusion schemes that combine the advantages of both methods (i.e., the efficiency and color constancy of the sample-based method with the ability of the statistical method to use the image of a different but somewhat similar scene as a reference image), using the correspondence between multiband sensor values and daytime colors (sample-based method) in a smooth transformation (statistical method). We designed and evaluated three new fusion schemes that focus on (i) a closer match with the daytime luminances; (ii) an improved saliency of hot targets; and (iii) an improved discriminability of materials. We performed both qualitative and quantitative analyses to assess the weak and strong points of all methods.

Recoloring textile fabric images based on improved fuzzy clustering

AbstractThis article proposes a new recoloring method for textile fabric images based on improved fuzzy local information c‐means (FLICM) clustering. In the clustering algorithm, the fuzzy factor was modified so that it can produce reliable segmentation in areas with rich details. With the obtained cluster labels and pixel‐wise memberships, the color of each pixel is modeled as the linear combination of the two most dominant colors. The recoloring process was then conducted by replacing the specified dominant color with user‐provided target colors. Experimental results showed that the proposed method can produce natural and faithful color appearance on both printed and yarn‐dyed fabric images, and outperforms the state‐of‐the‐art. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 115–123, 2017

A false color image fusion method based on multi-resolution color transfer in normalization YCBCR space

In this paper, a false color image fusion method for merging visible and infrared images is proposed. Firstly, the source images and reference image are decomposed respectively by Laplacian pyramid transform. Then the grayscale fused image and the difference images between the normalized source images are assigned to construct YCBCR components. In the color transfer step, all the three channels of the color space in each decomposition level are processed with the statistic color mapping according to the color characteristics of the corresponding sub-images of the reference image. Color transfer is designed based on the multi-resolution scheme in order to significantly improve the detailed information of the final image, and to reduce excessive saturation phenomenon to have a comparatively natural color appearance compared with the classical global-coloring algorithm. Moreover, the differencing operation between the normalized source images not only provides inter-sensor contrast to make popping the potential targets but also weakens the influence of the ambient illumination variety to a certain degree. Finally, the fused results and several metrics for evaluation of fused images subjectively and objectively illustrate that the proposed color image fusion algorithm can yield a more complete mental representation of the perceived scene, resulting in better situational awareness.

Infrared and Low-Light-Level Image Fusion Method Based on Sparse Representation and Color Transfer

A natural color fusion method for infrared and low-light-level image is proposed. This method utilizes image fusion and color transfer. The fused image uses sparse representation to merge the source images information to be assigned to the Y channel. And then the I and Q channel is combined using Toets method, which extracts the common component from the source images. Finally, the false-color image is obtained by using color transfer technology to the prior pseudo-color YIQ image. Experiments show that the result of our method is information that is more salient, has a higher color contrast, and a more natural color appearance when compared with those produced by the traditional coloration algorithm.

A Novel Color Image Fusion for Multi Sensor Night Vision Images

In this paper presents a simple and fast color fusion approach for night vision images. Image fusion involves merging of two or more images in such a way, to get the most advantageous characteristics of each image. Here the Visible image is fused with the InfraRed (IR) image, so the desired result will be single, highly informative image providing full information. This paper focuses on color constancy and color contrast problem. Firstly the contrast of the infrared and visible image is enhanced using Local Histogram Equation. Then the two enhanced images are fused in three compounds of a LAB image using aDWT image fusion. This paper adopts an approach which transfer color from the reference image to the fused image using Color Transfer Technology. To enhance the contrast between the target and the background, a scaling factor is introduced in the transferring equation in the b channel. Finally our approach gives the Multiband Fused image with the natural day-time color appearance and the hot targets are popped out with intense colors while the background details present with the natural color appearance.

Total nasal reconstruction with total rib cartilage framework

To investigate a new technique for nasal reconstruction with total rib cartilage framework. The expanded frontal flap was fabricated by skin expansion and flap delay to cover the reconstructed nose. The dorsal flap was reversed as the lining of reconstructed nose. The whole framework was made by rib cartilage. Secondary revision operation was also performed to make the reconstructed nose more natural. Total nasal reconstruction was performed successfully in 37 cases. Each patient underwent 4-7 operation during a period of 6-8 months. 32 patients were followed up for 12-24 months. The reconstructed nose had a natural skin color and symmetric appearance with good ventilation and less scar. Both doctors and patients were satisfied with the results. Satisfactory cosmetic result and ventilation function can be achieved by nasal reconstruction with total rib cartilage framework.

Color contrast enhancement for color night vision based on color mapping

The increasing availability and deployment of imaging sensors operating in multiple spectral bands has led to a large research effort in image fusion, bringing a lot of pixel-level color fusion algorithms. Color constancy and color contrast are two important topics for color image fusion. However, there is no work considering these two aspects in the meanwhile. The paper focuses on enhancing the color contrast between targets and their backgrounds and maintaining the color constancy. Firstly, a group of visible and infrared images are rendered with natural colors with color contrast enhancement algorithm. Then a color reference palette is derived from source images and their corresponding fused results. To enrich this palette, the nearest Euclidean distance determines the absent colors. The complete palette can be deployed in real-time to different multi-band image sequences of similar scenes. Experimental results based on different data sets show that the targets are popped out with intense colors while backgrounds present natural color appearance. Some objective analysis also shows that the presented method not only inherits more detail information from source images but also brings bigger color distance when comparing with the existing algorithms.

Fast color contrast enhancement method for color night vision

The increasing availability and deployment of imaging sensors operating in multiple spectral bands has led to a large research effort in color image fusion, resulting in a plethora of pixel-level image fusion algorithms. In this study a simple and fast fusion approach for color night vision is presented. The contrast of infrared and visible images is adjusted by local histogram equalization. Then the two enhanced images are fused into the three components of a Lab image in terms of a simple linear fusion strategy. To obtain false color images possessing a natural day-time color appearance, this paper adopts an approach which transfers color from the reference to the fused images in a simplified Lab space. To enhance the contrast between the target and the background, a stretch factor is introduced into the transferring equation in the b channel. Experimental results based on three different data sets show that the hot targets are popped out with intense colors while the background details present natural color appearance. Target detection experiments also show that the presented method has a better performance than the former methods, owing to the target recognition area, detection rate, color distance and running time.

Effective contrast enhancement method for color night vision

Image fusion refers to the techniques that integrate complementary information from multiple image sensors’ data in a way that makes the new images more suitable for human visual perception. The paper focuses on the low color contrast problem of linear fusion algorithms with color transfer method. Firstly, the contrast of infrared and visible images is enhanced using local histogram equalization and median filter. Then the two enhanced images are fused into the three components of a Lab image in terms of a simple linear fusion strategy. To enhance the color contrast between the target and the background, the scaling factor is introduced into the transferring equation in the b channel. Experimental results based on three different data sets show that the hot and cold targets are all popped out with intense colors while the background details present natural color appearance. Target detection experiments through target recognition area, detection rate, target-background discrimination also show that the presented method has a better performance than the former methods.

Morphological rational operator for contrast enhancement

Contrast enhancement is an important task in image processing that is commonly used as a preprocessing step to improve the images for other tasks such as segmentation. However, some methods for contrast improvement that work well in low-contrast regions affect good contrast regions as well. This occurs due to the fact that some elements may vanish. A method focused on images with different luminance conditions is introduced in the present work. The proposed method is based on morphological transformations by reconstruction and rational operations, which, altogether, allow a more accurate contrast enhancement resulting in regions that are in harmony with their environment. Furthermore, due to the properties of these morphological transformations, the creation of new elements on the image is avoided. The processing is carried out on luminance values in the u'v'Y color space, which avoids the creation of new colors. As a result of the previous considerations, the proposed method keeps the natural color appearance of the image.

具有深度感的彩色夜视图像生成方法

Depth perception for night vision (NV) imagery could largely improve scene comprehension. We present a novel scheme to give fused multi-band NV imagery smoothly natural color appearance as well as depth sense from color. Our approach is based on simulating color cues by varying saturation values of each object in the color NV image, in correspondence with the ratio between the infrared and low-light-level sensor outputs which in practice is the depth feature for same materials. We render the NV image segment-by-segment by taking advantage of image segmentation, dominant color transfer, saturation variation, and image fusion. Experiments have shown that the proposed scheme can achieve satisfying results.

Size Effect of the Immediate Surround for the Border between the Natural and Unnatural Object Color Appearance

The border luminance of the test stimulus between the natural and unnatural object color, y yn B u was obtained for different spatial sizes of the immediate surround to prove that n B u can be determined based on a new recognized visual space of illumination (RVSI) that is assumed to be constructed for the immediate surround separately from the RVSI for the subject’s room itself. The n B u of five test stimuli were determined for six different sizes covering from zero to 1866 cm2 with four different lightnesses, N4, N6 and N8, while keeping the room illuminance constant at 100 or 600 lx. The results showed that luminance of the border n B u gradually decreased as the size of the immediate surround was increased and that the decrease was larger for immediate surround with lower lightness. The results were interpreted as showing a new RVSI constructed for the spatial extent of the immediate surround of the test stimulus, and the RVSI was more completely constructed for larger spatial size of the immediate surround. © 2005 The Optical Society of Japan

ハイブリッドセラミックスによる臼歯部ジャケットクラウンの適合性に関する研究

Hybrid ceramics “Estenia” has appropriate mechanical strength and natural color appearance for posterior prosthesis. The purpose of this study was to evaluate the fitness of posterior jacket crowns fabricated by Estenia under different experimental conditions.Two types of epoxy abutments, normal and wide shoulder, of upper first molar were used in this study. In addition, five different conditions of die-spacer layering were used. The crowns and abutments wereembedded and sectioned buccolingually to measure the internal and marginal gaps between the crown and abutment.The marginal gaps ranged from 18.4 to 66.6 pmfor normal abutment and from 15.8 to 59.0 um for wide shoulder abutment. When the internal and marginal gaps of the normal abutments were compared with those ofwide shoulder abutments, no significant difference was found among the two typesof abutments.Under the conditions of this study and from the results, the following conclusions were reached:1. Estenia demonstrated clinical acceptability in fitness of posterior crowns.2. Marginal and internal fitness was not influenced by the types of abutment.3. Die-spacer application to internal line-angle of shoulder preparation was an effective method for decreasing marginaldiscrepancy.

ＩＰＳ Ｅｍｐｒｅｓｓの色調に関する研究 各種接着性レジンセメントによる色調の影響について

IPS Empress®, an all-ceramic crown system, achieves natural tooth color appearance, however, because of the light transmission itself, abutment tooth color is influenced by the final restoration.This paper describes the effect of color blocking and changing through background color when using nine adhesive resin cements (50 and 100μm) and four ceramic ingots (TI, TII, OI and OII), which have different light transmission with a thickness of 1.5 mm in the middle coronal tooth portion, in the staining technique. The results were as follows:1. The effect of color blocking was significantly improved when only using JO (IMPERVA DUAL Opaque) and PO (PANAVIA 21 Opaque) cementation insertion.2. According to the increase in thickness of resin cement of all specimens, the value of L* tended to decrease as the luminosity decreased, the value of a* did not significantly change, and the value of b* tended to increase and there was a tendency to become more yellow.3. As the effect of color blocking, specimens using Oil ingot with low light transmission had the highest value. As the influence of thickness through the resin cementation, T I ingot with higher light transmissionhad a significantly improved value.

ＣＣＭによるポーセレンラミネートベニアクラウンの色調構築 第２報 マスキングポーセレンの着色成分にデンティンを用いた場合の色調構築精度

Porcelain laminate veneer crown is an excellent system to improve the color of a discolored tooth in the anterior region having occlusal contact. Since masking porcelain of porcelain laminate veneer crown has opacity for hiding the discolored tooth, it was difficult to give a high translucency to the laminate crowns by conventional methods.The purpose of this study was to produce the natural color and excellent appearance of laminate crowns with adequate translucency using the Computer Color Matching (CCM) System to compensate opacity of masking porcelain.Construction of CCM sample, discolored layer, and procedure of CCM formulation are the same as part 1.In this study, 1 kind of opaque porcelain was used as the hiding element, and 3 kinds of dentin were used as the coloring element. According to the CCM formulation, masking porcelain was baked and the CCM samples were made.In comparison of the target color and CCM sample, both reflectance curves were very similar and color difference dE was under 3.0. Furtheremore, CCM samples showed the color to be indistinguishable from the target color by the naked eye.

ＣＣＭによるポーセレンラミネートベニアクラウンの色調構築 第１報 マスキングポーセレンの着色成分にオペークを用いた場合の色調構築精度

Porcelain laminate veneer crown is an excellent system to improve the color of a discolored tooth in the anterior region having occlusal contact. Since masking porcelain of porcelain laminate veneer crown has opacity for hiding the discolored tooth, it was difficult to give a high translucency to the laminate crowns by conventional methods.The purpose of this study was to produce the natural color and excellent appearance of laminate crowns with adequate translucency using the Computer Color Matching (CCM) System to compensate opacity of masking porcelain.Construction of CCM sample, discolored layer, and procedure of CCM formulation are the same as part 1.In this study, 1 kind of opaque porcelain was used as the hiding element, and 3 kinds of dentin were used as the coloring element. According to the CCM formulation, masking porcelain was baked and the CCM samples were made.In comparison of the target color and CCM sample, both reflectance curves were very similar and color difference dE was under 3.0. Furtheremore, CCM samples showed the color to be indistinguishable from the target color by the naked eye.