Michromatic scope for enhancement of color difference

A michromatic (microscope plus chromatic) scope is a device that enhances the color discrimination between two spectral color datasets. Three spectral filters are required, instead of the conventional red, green, and blue filters, for the implementation of a michromatic camera. In this study, we describe two approaches to the design of these filters: in the first case, the design is based on the direct optimization of the filter characteristics (transmittance), whereas in the second case, the design is based on the nonnegative tensor factorization (NTF) of the spectral datasets. A michromatic camera can be implemented using these filters along with compatible postprocessing in‐camera firmware. Here, we performed experiments with two color datasets: one comprising skin and vein colors, and one comprising skin and cosmetics colors. These were further divided into a training set and a test set. The filters were defined using the training set, and the operation of the filters was tested and magnified using the test set. Our experiments demonstrated that the proposed approaches are suitable for color discrimination. For the first color dataset, the enhancement produced using the optimized filters was up to 252% of the original value, and the average color difference ΔE was increased from 2.82 to 9.93. NTF and preprocessing further enhanced the ΔE up to 21.84. For the second color dataset, NTF and postprocessing enhanced the ΔE from 4.33 to 29.19. The proposed discrimination enhancement could be physically implemented in a designated digital charge‐coupled device camera with proper filter installation and compatible postprocessing. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2010     

Derivation of a color space for image color difference measurement

In digital image reproduction, it is often desirable to compute image difference of reproductions and the original images. The traditional CIE color difference formula, designed for simple color patches in controlled viewing conditions, is not adequate for computing image difference for spatially complex image stimuli. Zhang and Wandell [Proceedings of the SID Symposium, 1996; p 731–734] introduced the S‐CIELAB model to account for complex color stimuli using spatial filtering as a preprocessing stage. Building on S‐CIELAB, iCAM was designed to serve as both a color appearance model and also an image difference metric for complex color stimuli [IS&T/SID 10th Color Imaging Conference, 2002; p 33–38]. These image difference models follow a similar image processing path to approximate the behavior of human observers. Generally, image pairs are first converted into device‐independent coordinates such as CIE XYZ tristimulus values or approximate human cone responses (LMS), and then further transformed into opponent‐color channels approximating white‐black, red‐green, and yellow‐blue color perceptions. Once in the opponent space, the images are filtered with approximations of human contrast sensitivity functions (CSFs) to remove information that is invisible to the human visual system. The images are then transformed back to a color difference space such as CIELAB, and pixel‐by‐pixel color differences are calculated. The shape and effectiveness of the CSF spatial filters used in this type of modeling is highly dependent on the choice of opponent color space. For image difference calculations, the ideal opponent color space would be both linear and orthogonal such that the linear filtering is correct and any spatial processing on one channel does not affect the others. This article presents a review of historical opponent color spaces and an experimental derivation of a new color space and corresponding spatial filters specifically designed for image color difference calculations. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2010     

Optical implementation of spectral filtering for the enhancement of skin color discrimination

Light reflected from an object contains a range of information about its physical and chemical properties. Changes in the physical properties of an object can sometimes be evident as barely detectable changes of color. Our earlier study (Proceedings of the 15th Color Imaging Conference, Albuquerque, New Mexico, 2007. p 195–200) proposed a method for designing a spectral filter to enhance visual discrimination. Two filters were designed: one to discriminate skin and vein colors on human arms, and other to discriminate human facial colors in the presence and absence of cosmetics. In this study, the filters with theoretically designed spectral transmittances were implemented as real optical filters. Visual inspection of RGB color images taken with a digital camera through the developed optical filters showed clear enhancement of discrimination of two preselected colors. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2012     

A new color image space HRU related to the CIEL*a*b* color space

The color image space with one kind of merit color image scales (WIP) is derived using the psychophysical method of magnitude estimation method, usually used in visual assessment of color appearance, which can be used to describe the color image meanings of colors of works of art in parallel with those of people. The results show that a new color image space HRU is developed, and the relativity between this space and the CIEL*a*b* color space is also discussed. And, a good relationship between the HRU color image space and the CIEL*a*b* color space can be found. This may be of great advantage to the new color image space HRU in predicting the color image for single color based on the color space CIEL*a*b*. © 2009 Wiley Periodicals, Inc. Col Res Appl, 34, 452–457, 2009     

Applying image‐based color palette for achieving high image quality of displays

In the highly competitive display market, manufacturers continuously develop new technologies to improve the image quality of displays. However, color measurement and visual assessment are time‐consuming to production lines. A new method to measure and improve color quality of the displays automatically therefore, is urgently needed to the manufacturers. This article proposes a familiar color correction strategy to optimize the colors of different displays by means of creating an image‐based color palette which enables color correction for familiar objects (e.g., facial skin, blue sky, or green grass) in the multidisplay systems. To produce the image‐based color palette, the 8‐bit RGB value of each pixel in an image is transformed to L*d*n* (lightness/dominant color/nondominant color) color channels, and the dominant‐color regions in an image are subsequently extracted from the dominant color (d*) channel. The memory color data of familiar objects can be set in reference monitor in advance to determine the dominant color (d*) channel. Then a series of palette colors are generated around a displayed image. The color palette will be displayed as a target for two‐dimensional colorimeter shooting to obtain the measured color data. The familiar color correction model was established based on a first‐order polynomial regression to achieve a polynomial fit between the measured color data and the reference color data on the color palette. The proposed method provides a solution to correct familiar colors on a displayed image, and maintains the original color gamut and tone characteristic in the multidisplay systems simultaneously. It is possible to achieve the preferred intent of the displayed images by using the proposed familiar color correction method. © 2012 Wiley Periodicals, Inc. Col Res Appl, 39, 154–168, 2014     

Influences of psychological factors on image color preferences evaluation

To bring substantial benefits of image designing for image designers and image processing professionals, this study focused on the image samples taken by digital cameras and tried to explore the influence of psychological factors on image color preference. First, we collected 310 questionnaires to investigate the types of image that interest the people in Taiwan. The images that Taiwanese prefer were categorized into seven types: People, Scenery, Artificial Environment, Plants, Animals, Still Life, and Food. Then, based on the results of this survey, total 81 images were collected. Next, six psychological factors (Color Memory, Color Comfort, Colorfulness, Color Harmony, Color Image, Concerned Area) on image color preference were identified by the Delphi method and literature review and then developed into another survey. A total of 150 people, as subjects, took this survey and gave their evaluation according to their image color preferences. Finally, using multiple regression statistics, this study discussed the relationship between psychological factors and image color preferences. This study discovered that each psychological factor plays a different role in different image categories. For instance, Color Comfort plays the most influential role in the Scenery image. Color Harmony is influential in the Food and Plants image. Concerned Area, likewise, is important in the image categories of People, Artificial Environment, and Still Life. Based on the results of this research, it is suggested to take psychological factors into consideration when dealing with different image categories in obtaining the best color performance of images. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2010     

Quantitative evaluation of color harmony via linguistic-based image scale for interior design

In order to develop a computer-based color consultation system, a quantitative evaluation of color harmony for interior images is constructed by using a linguistic-based image scale. Conventionally, color harmony from any engineering perspective has received limited attention, because its successful evaluation requires the development of pleasure-related features. In this study, a new pleasure-related function of color linguistic distribution (CLD) is proposed to quantitatively represent the mental color impression of interior images upon a designed one-dimensional linguistic-based image scale of EXCITING-CALM. Supported by a database that includes fashion trends, the distribution state of CLD is capable of indicating the fashion trends in Taiwan. Also, on the image scale, the grade of color harmony can be measured by its CLD similarity to a reference harmony distribution (RHD). Evaluated results demonstrate that interior design is primarily dominated by (low) saturation and (high) brightness. Also, results based on CIE1976 L*a*b* and CIE1976 L*u*v* color spaces are observed to be better than those based on the hue-dominated method of Moon-Spencer theory in corresponding with human's linguistic similarity, questionnaire-based harmony evaluation, and social trends. Moreover, our solution percentage has been investigated as 72.3%, which is better than those of the Moon-Spencer theory and of the “Law of Inverse Ratios of Areas.” For application purposes, the proposed system is suitable to analyze the mental impression of products from the perspective of the customer. © 1996 John Wiley & Sons, Inc.     

Research on product color design decision driven by brand image

As one of the most important visual characteristics in a product system, color can arouse the user's emotional demands quickly. Due to the complexity of the user's emotional needs mining process, it can be expressed by color image adjectives. Meanwhile, product color trends that meet the user's emotional demands may help decision makers to anticipate a new market positioning and reduce the blindness in the product color design. In this study, the Gray theory combined with the Kansei engineering was used to mine the macro and microscopic factors in product color design decision process based on the product color brand image. The results showed that the constructed method could be used to guide the product color design that was to meet the user's emotional needs comprehensively and quickly. The method solved the problems that exist in the current product color trend prediction research and improved the accuracy of the correlation mining between product color design elements and brand image. Lastly, the color design of the mid-range sedan was taken as an example to prove the feasibility of the research approach. This is a new attempt to guide product color design decisions in two aspects, one is known from the results of product color trends quantitative prediction, and the other one comes from the correlation calculation between product color design elements and brand image.     

Color separation for improved perceived image quality in terms of graininess and gamut

Multi‐channel printing employs additional inks to improve the perceived image quality by reducing the graininess and augmenting the printer gamut. It also requires a color separation that deals with the one‐to‐many mapping problem imposed when using more than three inks. The proposed separation model incorporates a multilevel halftoning algorithm, reducing the complexity of the print characterization by grouping inks of similar hues in the same channel. In addition, a cost function is proposed that weights selected factors influencing the print and perceived image quality, namely color accuracy, graininess and ink consumption. The graininess perception is qualitatively assessed using S‐CIELAB, a spatial low‐pass filtering mimicking the human visual system. By applying it to a large set of samples, a generalized prediction quantifying the perceived graininess is carried out and incorporated as a criterion in the color separation. The results of the proposed model are compared with the separation giving the best colorimetric match, showing improvements in the perceived image quality in terms of graininess at a small cost of color accuracy and ink consumption. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 486–497, 2017     

Study on the preference of city color image selection based on the logistic model: A case study of Shanghai

With the continuous progress of urbanization, China's urban color planning has begun to receive attention, but there are still many problems in the quality of color environment. In order to clarify further the urban color positioning of our country, the detailed urban color planning objectives are set up, and the opinions of residents with different attributes are included in the consideration scope of urban color planning objectives, so as to guide the future urban color planning scientifically. From the perspective of urban residents' preference, this article takes Shanghai as an example to analyze the difference of residents' preference for urban color selection with different attributes. In this article, the logistic regression model was used to analyze the results of residents' choice, so as to conclude that the significant factors influencing residents' preference for city color image include age, monthly income, current city of residence, frequency of coming to Shanghai and whether they have been to other countries. Therefore, paying attention to the above significant attributes of residents and carrying out in-depth research can provide reference value for the status of the city's future color image.     

Assessing the application of an image color appearance model to basic self‐luminous scenes

Image color appearance models (Image CAMs) have been developed to predict the perception of complex scenes and are mainly used for image rendering and video reproduction applications. Among these Image CAMs, iCAM is an Image CAM that takes an image as the input and provides the perceptual attributes for each pixel. On the other hand, nonimaging CAMs are widely used and validated, but they always assume a simple test scene of a uniform flat stimulus, a quasi‐neutral background, and a surround. This study presents an evaluation of the performance of iCAM when applied to these simple self‐luminous scenes in predicting the influence of background luminance, background size, saturation, and stimulus size on stimulus brightness. The results show that iCAM is capable of predicting the effect of background luminance and some background size scenarios. However, for unrelated self‐luminous stimuli (dark background), the model predictions do not match the reference data. An evaluation of the effect of the filter kernel size and its relation to the physiological mechanism of image processing inside the visual system has been investigated. Furthermore, the impact of saturation and stimulus size on brightness seems to be underestimated by the model, because the Helmholtz‐Kohlrausch and stimulus size effects are not included. Hence, these findings call for an enhanced Image CAM.     

基于模糊聚类的彩色图像分割算法

提出了基于HSV空间的模糊聚类彩色图像分割算法。运用模糊C方法（FCM fuzzy clustering measure模糊聚类方法）对颜色量化后的图像进行聚类,结合了彩色图像的色彩和空间信息的特点,并且对聚类结果进行了合并优化,去除了聚类过于细小的部分。     

基于图像技术的化学需氧量检测研究

为了准确、快速分析水质中化学需氧量(COD),在分光光度法基础上,提出根据图像颜色特征值测量COD的方法 ,同时开发了基于图像技术的检测装置。以该装置为平台,进行了水质COD测定条件的优选,并在优选条件下建立最佳颜色特征值与COD浓度的关系模型。最后进行重复性检测和测量结果对比分析。结果表明:该方法相关系数R~2=0.995 26,检测范围为40~550 mg/L。该装置比国标法和快速法测COD操作简便,并具有较高的准确性。     

基于图像颜色特征的涂层老化失效检测方法

结合数字图像技术和色度学相关原理,针对腐蚀过程涂层表面出现的色彩变化,建立了基于颜色特征的涂层材料腐蚀性能检测方法。利用建立的腐蚀形貌采集系统,对现场暴露不同时期的涂层试片进行采集。采用HSV颜色空间对腐蚀试样表面的变色程度进行描述,提出颜色特征参数CP,实现对涂层腐蚀试样外观变色的计算机判别,为材料的腐蚀特征检测提供了新的方法。     

Skin‐color correction method based on hue template mapping for wide color gamut liquid crystal display devices

The development of wide color gamut (WCG) liquid crystal display (LCD) plays an important role in the high‐quality television (TV) field. Nowadays, people want their TV or display devices to have the capability of showing vivid colors while keeping skin colors as natural as they remember. Therefore, it is necessary to develop color‐correction technologies for WCG LCD system. A new color‐correction method named “natural skin‐color mapping algorithm” (NSCMA) for WCG LCD is proposed in this study. It can solve the skin‐color contour problem in color‐corrected images with simple skin‐color detection. Its development is based on the concepts of performing color mapping between source hue colors and target hue colors on each hue page. The polynomial regression is also applied to calculate the color mapping conversion matrices. Two color mapping factors called template‐size factor and tone‐compression factor are designed in NSCMA. The template‐size factor is used to adjust target template sizes adequately. The tone‐compression factor is designed to control the degrees of image enhancement. For facial skin‐color pictures, the appropriate settings of template‐size factor and tone‐compression factor will get suitable color image rendering on the WCG LCD. It is demonstrated that the WCG LCD can be corrected to show vivid color pictures and keep facial skin colors as natural as possible when the proposed NSCMA is performed. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2011     

Media‐dependent color appearance modeling based on artificial neural networks

In this study, we tried to consider various color appearance factors and device characterization together by visual experiment to simplify the across‐media color appearance reproduction. Two media, CRT display (soft‐copy) and NCS color atlas (hard‐copy), were used in our study. A total of 506 sample pairs of RGB and HVC, which are the attributes of NCS color chips, were obtained according to psychophysical experiments by matching soft copy and hard copy by a panel of nine observers. In addition, a set of error back‐propagation neural networks was used to realize experimental data generalization. In order to get a more perfect generalizing effect, the whole samples were divided into four parts according to different hues and the conversion between HVC and R_HVCG_HVCB_HVC color space was implemented. The current results show that the displays on the CRT and the color chips can match well. In this way, a CRT‐dependent reproduction modeling based on neural networks was formed, which has strong practicability and can be applied in many aspects. © 2006 Wiley Periodicals, Inc. Col Res Appl, 31, 218–228, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20209