基于色貌模型CIECAM02和CIECAM16的观察者色觉差异研究

为研究现有CIECAM02和CIECAM16色貌模型对个体观察者颜色分辨的计算性能,选用了5个光谱功率分布不同的照明光源和GretagMacbeth ColorChecker标准色卡的24个颜色,代入208套个体观察者颜色匹配函数,量化计算不同观察者的色觉差异.两个色貌模型中,对于所有选用的照明光源和颜色中心,个体观察者与标准观察者CIE1964的CIECAM-UCS色差平均值相同,均为1.29.同时,两个色貌模型中,观察者间离均色差表现较为一致,在白光LED光源下观察者间差异性相对较大,且在蓝色中心处获得最大值,为2.49(2.32),表明在该观察条件下,不同观察者间颜色感知偏差较大.研究结果可为色貌模型的修正提供基础数据和计算依据.     

基于视觉感知模型的彩色图像分割框架

图像分割是图像理解和识别的重要基础。目前,彩色图像分割有3个问题有待解决：无法处理有空间频率变化的图像;没有考虑图像的观察条件和颜色细节;对颜色空间的依赖性较大。本文提出了一个基于视觉感知的图像分割框架。此框架利用人眼视觉灵敏度函数模仿人眼的视觉模糊机制,能有效处理有空间频率变化的图像;使用CIECAM02来预测复杂观察条件下的图像色貌;最后应用不同的色差公式实现基于颜色相似性的分割算法。实验结果证明本文框架可以产生比传统算法更适合于人类感知的分割结果。     

CIECAM02色貌模型应用存在的问题及建议解决的方法

综述了CIECAM02色貌模型应用已经确定的问题以及建议解决的方法,包括明度计算问题、黄一蓝问题和紫色问题导致数学计算不稳定,以及ICC色彩管理系统中应用CIECAM02模型在色域映射、HPE矩阵产生的白色适应和模型逆变换中遇到的困难.可以看出,虽然对出现的问题提出了相应的解决方法,但这些方法还需要在不同应用目的中检验...     

改进直方图匹配和自适应均衡的水下图像增强

为了更有效地改善水下图像的颜色,进一步提升图像的对比度和清晰度,提出改进直方图匹配和自适应均衡的水下图像增强方法。以像素均值最大的通道图像的直方图作为基准,对各通道图像分别进行直方图匹配,校正水下图像的颜色偏差;充分利用HSI颜色空间中颜色分量与明度分量的独立性,对明度分量进行自适应的局部直方图均衡化,进一步提升图像的对比度和清晰度。主、客观的实验数据显示,相对于部分现有方法,本文方法对水下图像增强后的视觉效果更优,信息熵、平均梯度、水下图像质量指标（Underwater Image Quality Measures, UIQM）和结构相似性指数（Structural Similarity Index Measure, SSIM）的值更高。因此,本文方法对水下图像具有更有优的增强效果。     

基于视觉感知模型的彩色图像分割框架

图像分割是图像理解和识别的重要基础.目前,彩色图像分割有3个问题有待解决:无法处理有空间频率变化的图像;没有考虑图像的观察条件和颜色细节;对颜色空间的依赖性较大.本文提出了一个基于视觉感知的图像分割框架.此框架利用人眼视觉灵敏度函数模仿人眼的视觉模糊机制,能有效处理有空间频率变化的图像;使用CIE CAM02来预测复杂观察条件下的图像色貌;最后应用不同的色差公式实现基于颜色相似性的分割算法.实验结果证明本文框架可以产生比传统算法更适合于人类感知的分割结果.     

基于光谱重建技术的壁画颜色复原与评价

为了在给定的照明和观察条件下，用相机响应信号重建物体表面光谱反射率，实现颜色的高精度复原，采用了多光谱成像技术采集物体表面的多光谱图像，使用主成分分析、 R 矩阵和正则化 R 矩阵方法进行了光谱反射率重建的理论研究，并对壁画色块颜色复原进行了实验验证，取得了壁画色块的重建光谱和颜色复原数据，同时对基于正则化 R 矩阵方法的壁画色块颜色复原结果进行了评价。结果表明，正则化 R 矩阵方法进行光谱重建的光谱精度和色度精度更高，与主成分分析和 R 矩阵方法相比，色差降低了0.0732，适应度系数提高了1.10%，均方根误差降低了0.0035，光谱匹配偏指数降低了0.0225。该方法能够满足高精度颜色再现的需要，适用于文物艺术品数字化存档、文物艺术品修复等领域。     

孟塞尔颜色体系在LED图像显示中的应用探讨

目前LED显示屏图像的光学参数都采用仪器测量,不能代表人眼主观感受。而孟塞尔颜色体系基于人眼主观视觉特性,明确给出了客观亮度因数与人眼明度值的非线性关系,以及颜色亮度的不可加性。由此对LED显示屏进行1校正和颜色修正,能够更加人性化地体现图像效果。     

多摄像机在无重叠区域的目标匹配算法

基于颜色特征的目标匹配方法具有很好的区分性和直观性,但是特征本身受光线变化、背景复杂度等影响而对于目标识别准确率存在差异.针对这一现状,提出了一种新的基于时空局部特征和颜色特征的目标匹配方法.利用时空局部特征3-D LSK对待测视频中的运动目标进行行为识别,识别出具有相同行为目标.再结合目标的颜色特征,通过基于区域权重(Weighted Region Matching)的颜色匹配方法来识别出具有相同颜色的目标.对无重叠区域的多个测试视频进行的相关实验表明,该算法能够有效识别出普通场景下的不同目标,对于衣着颜色相近的不同目标也有很高的识别率.     

基于颜色直方图与SIFT多层次图像匹配检测

图像的匹配检测是计算机视觉领域的重要研究内容,是很多图像理解系统中的重要组成部分。实际应用中,图像的匹配检测受到光照变化,视角变化,局部遮挡,运算量巨大等因素的影响。本文提出了一种先进的半自主基于图像颜色直方图与SIFT特征的多层次图像匹配检测方法。首先使用图像的颜色直方图特征匹配确定模板图像在待配图像中的候选区语,再在候选区域中寻找SIFT特征,并进行匹配检测。实验结果证明了我们的方法的有效性与鲁棒性。     

一种新的快速立体视觉导航算法

立体视觉技术被广泛的应用于视觉导航系统中.由于要求计算快速,以往的立体视觉导航系统通常采用局部匹配的方法,其匹配精确度较差,不能满足高性能视觉导航的需要.为此,我们提出了一种新的快速立体视觉匹配算法,该算法将每一条外极线分割成亮度一致的线段,并采用全局的树型动态规划进行优化求解,既充分利用了全图的相关信息,取得了较高的匹配准确度,又减少了搜索变量的个数,使得系统的效率得到大幅度的提高.实验结果表明,该算法能够取得与基于MRF的全局网格匹配算法相当的匹配结果,而执行时间上却很快,为视觉导航提供了可靠的环境三维数据.     

Psychophysical evaluation of gamut mapping techniques using simplerendered images and artificial gamut boundaries

Using a paired comparison paradigm, various gamut mapping algorithms were evaluated using simple rendered images and artificial gamut boundaries. The test images consisted of simple rendered spheres floating in front of a gray background. Using CIELAB as our device-independent color space, cut-off values for lightness and chroma, based on the statistics of the images, were chosen to reduce the gamuts for the test images. The gamut mapping algorithms consisted of combinations of clipping and mapping the original gamut in linear piecewise segments. Complete color space compression in RGB and CIELAB was also tested. Each of the colored originals (R,G,B,C,M,Y, and Skin) were mapped separately in lightness and chroma. In addition, each algorithm was implemented with saturation (C(*)/L(*)) allowed to vary or retain the same values as in the original image. Pairs of test images with reduced color gamuts were presented to twenty subjects along with the original image. For each pair the subjects chose the test image that better reproduced the original. Rank orders and interval scales of algorithm performance with confidence limits were then derived. Clipping all out-of-gamut colors was the best method for mapping chroma. For lightness mapping at low lightness levels and high lightness levels particular gamut mapping algorithms consistently produced images chosen as most like the original. The choice of device-independent color space may also influence which gamut mapping algorithms are best.     

Tone mapping with contrast preservation and lightness correction in high dynamic range imaging

In real-world environments, the human visual system perceives a wide range of luminance in a scene. However, the full range of tones in a high dynamic range (HDR) scene cannot be displayed on standard display devices due to their low dynamic range (LDR). Therefore, tone mapping is necessary to faithfully display a HDR scene on an LDR display device. Existing tone mapping methods have problems because details and contrast in a scene are not preserved faithfully, and they also distort the colors in a scene. Thus, we propose a tone mapping method for preserving the detail in an HDR scene using a weighted least squares filter, which preserves the global contrast in a scene by using a competitive learning neural network, before applying a tone reproduction operator to preserve the color without shifting the lightness. According to the Helmholtz–Kohlrausch effect, the perception of brightness depends on the lightness, chroma, and hue of a color. For example, the luminance of pixels with specific colors such as red and blue is low in an HDR scene. The proposed method corrects the lightness of pixels according to the color (i.e., lightness, chroma, and hue) of a tone-mapped image. Experimental results with several test sets of images demonstrated that the proposed tone mapping method with contrast preservation and lightness correction is more suitable for dynamic range compression than existing tone mapping methods, while it also preserves the color of a scene in an effective way.     

Perceptual strength of 3-D crosstalk in both achromatic and color images in stereoscopic 3-D displays

The cognitive strength of crosstalk in stereoscopic 3-D displays is investigated, and new quantitative analysis methods based on color difference and grayscale levels are developed. Unlike results using existing metrics, results by the new methods agree well with the perceived crosstalk strength in achromatic images with various levels of grayscale. The crosstalk in color images, which has not been studied before, exhibits interesting results in that the crosstalk metric based on the lightness difference expresses the best fit with the perceptual crosstalk when the intended image is black and the chroma value of the counterpart image is large, but the metric using the color difference works better when the intended image is not black. The new metrics reveal that the difference between active and passive 3-D displays is not as large as suggested by conventional crosstalk metrics, and the crosstalk in color images cannot be simply estimated by averaging the crosstalk of red, green, and blue subpixels. The new metrics will be useful in the development of new image processing technology and display technology for better image quality.     

Compensation of de-saturation effect in HDR imaging using a real scene adaptation model

The iCAM06, a high dynamic range rendering process, contains chromatic adaptation method based on the CIECAM02 model. The D factor, degree of adaptation, in the chromatic adaptation of the iCAM06 is the function of the adapting luminance level, but it does not consider the visual white point shift according to the variation of luminance level. The iCAM06 acquires a blurred illuminant image. So, each pixel has a different illuminant color. When some of the colors cover the entire image, a de-saturation effect appears around these colors. The simply modified D factor to reduce the de-saturation effect causes unsuitable changes in the degree of adaptation. Therefore, we propose a new method to find the global illuminant information and the D factor for the illuminant in the HDR image rendering process. Comparing the proposed with the conventional method, we confirm that the proposed method provides better illuminant estimation and color representation.     

数字电视颜色管理术语

近年来,国际上对扩大摄取和重现彩色图像颜色范围和改善视觉效果很重视,ISO和IEC已制订相关标准,而中国国内对此尚未引起足够关注。汇总和筛选了科研工作中积累的数字电视颜色管理术语,共100余条。着重选取了近年出现或不够常见、含义不清、容易混淆的词条。对某些不够规范的称呼建议了中文名称。各词条给出了对应的英文表述。词条名称以下,第一段为定义或对应的标准,其他段为简要解释,相关数据等。文字力求规范,数据力求准确,希对规范、管理和改善数字电视图像色度性能有一定参考价值。     

Application of the CIECAM02 colour appearance model to predict the effect of gamma on the colours viewed on CRT monitors

The purpose of this investigation is to develop a prediction process for the subjective response of human viewers to the colours of a range of samples displayed on a CRT (cathode ray tube) monitor, for a range of different values of monitor gamma.

We have used the gain-offset-gamma (GOG) model of the behaviour of the CRT, together with the assumption of “standard” CRT colorimetry, to permit an assessment of the influence of monitor gamma on the appearance of the colours reproduced on its screen. Colour differences have been computed in a colour space, based on the CIECAM02 colour appearance model, here termed the (J,a_C,b_C) colour space.

A total of 76 numerically defined colour samples were used, and were subjected to the influence of eight different gamma values. The results show that there can be significant colour appearance differences as a consequence of erroneous CRT gamma values. Such errors in colour appearance are highly likely to present problems when dealing with applications where an accurate impression or understanding the displayed colour is important.     

LED显示屏的色度均匀性和色保真度

全彩色LED显示屏的均匀性包括亮度均匀性和色度均匀性两个方面。均匀性不好，显示屏就会出现”花斑”或”马赛克”，严重影响图像的观看效果。其中色均匀性包括均匀性和色保真度两个方面。色均匀性是指同屏各个象素、模块和模组之间显示同一种颜色时的色差：色保真度则是指显示屏上的图像与源图像或源景物之间的色重现的吻合程度。这两个问题都涉及到LED色差的原因和计量，为了提高色均匀性和色保真度，必须减少色差，为此研究了进行色修正和补偿的方法。     

长期视频监控系统的多分布模型背景差方法

提出在长期视频监控系统中采用背景差进行运动目标提取时算法所要满足的基本要求，并提出了一种能够满足这些要求的背景差方法。该方法用色度、亮度窨的多个分布模型来建立背景模型，描述彩色视频图像的背景像素点及其统计特性，在对背景模型更新的时将均值、方差的更新速率和多个模型的更替速率分开。对像素值属于多个分布模型的情况，用最小相似距离确定更新的模型。该方法利用提取的前景像素点信息反馈以检测光强的突变，利用亮度信息消除运动目标的阴影。实验证明该方法很好的满足了长期视监控系统的要求。