基于图像分割和区域匹配的灰度图像彩色化算法

针对传统颜色传递算法只进行全局颜色传递,未考虑图像局部特征,出现颜色误传递的问题,提出了一种基于Graph-Based图像分割与区域匹配的灰度图像彩色化算法。利用Graph-Based图像分割将目标图像和参考图像分割为若干个亮度和纹理特征一致的子区域。根据本文提出的思想,认为"具有相似亮度和纹理的子区域具有相似的颜色分布",对目标图像和参考图像的子区域建立匹配关系,利用亮度特征和LBP局部纹理特征对子区域进行匹配。最后,在YCbCr颜色空间中对相匹配子区域利用亮度和纹理特征进行颜色传递。实验结果证明,在该算法中其参考图像无需和目标图像配准,只需特征相近,就可以对目标图像实现全自动的彩色化技术并有效克服了颜色误传递的现象,彩色化结果图像在色彩分布和主观视觉上都有明显的提高。     

基于小波变换和彩色变换的多聚焦图像融合

提出一种结合小波变换及彩色空间变换的多聚焦图像融合方法。首先把彩色图像从RGB空间变换到YIQ空间,将颜色分量与亮度分量进行分离,从而克服RGB空间各颜色分量的相关性造成融合后图像颜色信息的丢失和错乱;接着,将待融合的多聚焦图像进行小波分解以刻画图像的多尺度信息,在小波域实现融合处理。在融合策略的选取上,对高频分量与低频分量分别采取局部方差与局部梯度最大的融合规则,同时以亮度分量Y作为衡量标准,通过一致性检测对融合系数做进一步的优选,以保持融合后图像的区域连续性。实验表明,该方法的融合结果无论在视觉质量及定量指标上都明显优于传统方法。     

基于亮度自适应分段的高动态图像色调映射算法

高动态范围图像(High Dynamic Range Image,HDRI)反映了真实场景的亮度值范围,具有较大的动态范围,而传统的显示设备的动态范围较低.若将高动态范围图像直接压缩到低动态范围显示设备时,可能会导致图像失真、细节丢失等问题.为解决上述问题,本文提出一种基于亮度自适应分段式的色调映射算法.首先,将高动态范围图像从RGB彩色空间转化到CIE XYZ彩色空间,使得亮度信息和彩色信息分离,并只对亮度信息进行处理且不改变颜色信息.其次,以对数亮度平均值作为关键值,从而得到划分区间段的低光区阈值和高光区阈值.然后,针对不同阶段亮度值的特点采用不同的亮度压缩算法,获得新的亮度分量.最后,恢复颜色信息,得到低动态范围图像.实验结果表明,本文的色调映射算法得到的结果整体亮度和细节效果较好.     

自适应HSV空间Retinex煤矿监控图像增强算法

针对煤矿井下的监控图像由于粉尘、煤尘、低照度或点光源等光照的影响,而整体阴暗模糊,对比度低,背景噪声强,视觉效果不理想的问题,提出一种改进的HSV(Hue,Saturation,Value)空间的颜色可恢复的多尺度Retinex(Muhi-Scale Ret-inex,MSR)的图像增强算法.该算法先将图像从RGB空间转换到HSV空间,以确保后续图像增强处理不会影响图像的色彩效果;然后利用提出的自适应的高斯核函数分离亮度分量V的照度分量和反射分量,再利用自适应的增益系数对反射分量进行增强处理,获得不受光照影响的、增强的反射图像;最后将反射图像逆变换回RGB空间,再利用优化的颜色恢复函数对增强的图像进行颜色修正,从而改善图像的全局视觉效果和局部对比度.实验表明该方法能有效提高煤矿井下监控图像的对比度和亮度,抑制背景噪声,从而大大改善煤矿井下监控图像的视觉效果,且很好地实现了参数自适应,减少了人为因素对结果的影响.     

基于结构光的高反物体三维形貌测量方法

提出了一种用于大面积高反物体的三维形貌测量方法。基于双色反射模型理论,提取了相机采集的条纹图像的漫反射分量,通过改进的反射分量分离算法对图像进行反射分量分离;对反射分量分离产生的图像空洞采用改进的种子填充算法进行修补;用三步相移结合质量引导算法得到连续相位,由系统标定的相位高度映射关系得到物体的高度信息。实验结果表明:所提方法实测误差约为0.23 mm,消除了93%～97%的高光像素,有效克服了反射光的干扰,对大面积反射光具有较好的稳健性。     

适于多种反射现象的光照估计方法

增强现实技术是将虚拟物体叠加到真实环境中,为了使虚拟物体更逼真地融入到环境,就需要估计场景中的真实光照。文中针对同时存在漫反射和镜面反射的场景或只存在漫反射的场景,提出了一种适于多种反射现象的光照估计方法。该方法使用相机拍摄多幅视角图像,通过检测每幅视角图像的镜面高光点来识别场景中是否存在镜面反射。若不存在镜面反射,则采用单张漫反射图像估计光照算法进行多幅视角图像光照估计。反之,若存在镜面反射则以镜面反射提供的信息为先验知识,再结合漫反射光照估计方法得到最终的光照估计结果。实验结果表明,文中方法提高了多种反射现象的光照估计的准确性。     

确定区域的人脸彩色传递

在对整幅图像色彩传递算法的基础上,提出了确定区域的人脸彩色传递法。首先利用改进的主动形状模型(ASM)方法定位人脸特征点,进而利用区域生长法确定人脸区域。在将参考图像和目标图像(彩色或灰度图)转换到去相关的对立色空间(lαβ颜色空间)后,对于彩色目标图像,分别调整肤色区域图各通道的均值和标准差;对于灰度目标图像,用亮度邻域统计量匹配的方法在参考图像中选取匹配点,并将匹配点的颜色赋值给目标图像中的对应点。最后,把传递结果转换到RGB颜色空间显示。实验结果表明,该方法能有效传递肤色,形成自然逼真的彩色人脸图像。     

红外偏振与红外光强图像的伪彩色融合研究

针对RGB和lαβ间转换过程复杂,运算速度慢,不便于用灰度融合图像直接代替亮度分量的问题,提出了一种基于YCαCβ空间的伪彩色融合方法.该方法首先对源图像进行基于特征差异的颜色映射,所得RGB图像通过YCαCβ变换提取亮度分量Y;然后采用新的融合规则对红偏振与光强图像进行了支持度融合,其中低频和高频分别采用目标背景分割和区域方差最大的融合规则;最后用融合结果代替亮度分量,再与Cα,Cβ分量进行YCaCβ逆变换,得到伪彩色图像.实验结果表明,与文献[8]方法比较局部方差提高21.5％、对比度提高1.15％、清晰度提高6.05％、运算速度提高30.5％,证明了本文算法的可行性和有效性.     

基于Choquet模糊积分的运动目标检测算法

本文提出了一种基于Choquet模糊积分的运动目标检测算法（CIMOD, Choquet Integrate-based Moving Object Detection）。将模糊测度和模糊积分理论应用于运动目标与背景分类中,提出了自适应阈值的Choquet积分算法,实现了图像的颜色特征和纹理特征相融合;选择YCbCr颜色空间代替传统RGB空间,将图像亮度与色度分离,降低了光照变化对运动检测的影响;利用局部二元模式（LBP,Local Binary Pattern）纹理特征对亮度级的单调的变化具有不变性的特点,将其融合到检测算法中,有效抑制了阴影的干扰。仿真实验结果表明,即使在光照变化、阴影干扰等复杂背景情况下,该算法也能够准确的检测出运动区域。     

YUV空间中基于稀疏自动编码器的无监督特征学习

现有无监督特征学习算法通常在RGB色彩空间进行特征提取,而图像和视频压缩编码标准则广泛采用YUV色彩空间。为了利用人类视觉特性和避免色彩空间转换所消耗的计算量,该文提出一种基于稀疏自动编码器在YUV色彩空间进行无监督特征学习的方法。首先在YUV空间随机采集图像子块并进行白化处理,然后利用稀疏自动编码器进行无监督局部特征学习。在预处理阶段,针对YUV空间亮度和色度通道相互独立的特性,提出一种将亮度和色度进行分离的白化措施。最后用学习到的局部特征在大尺寸图像上进行卷积操作从而获得全局特征,并送入图像分类系统进行性能测试。实验结果表明：只要对亮度分量进行适当的白化处理,在YUV空间中的无监督特征学习就能够获得相当于甚至优于RGB空间的彩色图像分类性能。     

A new class of chromatic filters for color image processing. theory and applications

This paper advances a new framework for chromatic filtering of color images. The chromatic content of a color image is encoded in the CIE u'v' chromaticity coordinates whereas the achromatic content is encoded as CIE Y tristimulus value. Within the u'v' chromaticity diagram, colors are added according to the well-known center of gravity law of additive color mixtures, which is generalized here into a nonlinear filtering scheme for processing the two chromatic signals u' and v'. The achromatic channel Y can be processed with traditional filtering schemes, either linear or nonlinear, depending on the specific task at hand. The most interesting characteristics of the new filtering scheme are: 1) the elimination of color smearing effects along edges between bright and dark areas; 2) the possibility of processing chromatic components in a noniterative fashion through linear convolution operations; and 3) the consequent amenability to computationally efficient implementations with fast Fourier transform. The paper includes several examples with both synthetic and real images where the performance of the new filtering method is compared with that of other color image processing algorithms.     

A spatially variant total variational model for chromatic aberration correction

In this paper, we propose a spatially variant total variational model to correct chromatic aberration (CA) that causes false color artifacts near edges in captured images. In general, it may be very difficult to determine suitably CA regions in captured images. Instead of using local image processing methods, our idea is to make use of spatially variant model to control the gradient and intensity matching between the red and blue color channels and the green color channel at the edges. The total variation regularization is also employed to constraint the change of the intensity of red and blue color channels during the gradient and intensity matching. We present both theoretical results and algorithms for the proposed model. Experimental results are given to illustrate the effectiveness of the proposed model and algorithm and show that their corrected images are visually better than those corrected by the other testing methods.     

一种适于镜面反射表面的从明暗恢复形状算法

为了实现镜面反射表面快速重构的需求,提出了一种基于高阶Fast Marching方法的从明暗恢复形状算法。首先假定光源为点光源,且位于无穷远处,其次认为摄像机遵循正交投影,其方向与光源方向保持一致,接着使用Blinn-Phong模型来描述镜面反射表面的反射特性,建立基于Blinn-Phong反射模型的镜面表面图像辐照度方程,然后将该辐照度方程转化为含有高度信息的Eikonal偏微分方程,利用高阶Fast Marching方法计算上述Eikonal方程的解,从而获得镜面反射表面的三维形状。实验结果表明:提出的方法可以快速精确地实现镜面反射表面的三维重构。     

基于结构光的镜面/漫反射复合表面形貌测量

光学三维测量技术以其非接触、无损及快速测量的优势被广泛应用于不同领域。已有的条纹投影和条纹反射测量术分别适用于漫反射表面和镜面表面。然而,航空航天和先进制造中存在许多漫反射和镜面反射表面同时存在的复合反射表面。提出一种基于结构光投影和反射的方法来实现复合表面形貌的快速测量。首先,投影仪投射蓝色正弦条纹图于被测物体表面,同时显示屏显示的红色条纹被镜面部分反射。其次,彩色相机采集经被测表面调制的变形条纹图。然后,从相机不同颜色通道中提取对应不同类型反射表面的变形条纹,并计算变形条纹图的绝对相位。最后,通过系统标定建立相位信息与深度之间的直接关系,得到被测复合表面的三维形貌。实验结果表明:该方法不仅能够有效地实现非连续复合表面物体的测量,还能够同时测量独立的漫反射和镜面反射表面的三维形貌。     

Gamut mapping optimization algorithm based on gamut-mapped image measure (GMIM)

This paper presented a novel gamut mapping optimization algorithm based on a special designed gamut-mapped image measure (GMIM). We formulated GMIM as an objective function in an iterative manner, where the iterative step changes based on the information weight which can be computed between the original image and the initial gamut-mapped images. A new metric, GMIM, is developed to compute the achromatic differences and the chromatic differences of the input images based on structural similarity index. For the achromatic part, we introduce the gradient information to detect the achromatic distortions between two images; the chromatic part aims to analyze the hue and chroma information. Further, the circular statistical theory is employed to calculate the hue value. In the iterative process, we change the iterative steps according to the information weight which can be computed by the information theory. The information map between images indicated regions in an image which human paid attentions to. Experimental results demonstrated that our new gamut mapping method can preserve the brightness, color, as well as detail information of the reference images.     

Colorimetrically accurate gray component replacement using the additive model

In four color printing, gray component replacement (GCR) is a method of replacing the achromatic component of a mixture of chromatic inks by a corresponding amount of the achromatic ink. Simple approaches to GCR lead to unacceptable color shifts. In this paper, the method using multiple processing steps is proposed. The novelty of the proposed method is augmentation of masking equations, which allows finding solutions for a pre-set amount of the black ink. The method performance was evaluated and compared with state of the art commercial solution. The experiments have shown that the proposed model is on average capable of achieving 40–55% ink savings with median colorimetric difference of less than 0.3, thus preserving the visual appearance of images.     

Saliency-directed color image segmentation using modified particle swarm optimization

Color image segmentation, an ill-posed problem, can be treated as a process of dividing a color image into some constituent regions and each region is homogeneous. In this study, a saliency-directed color image segmentation approach using “simple” modified particle swarm optimization (PSO) is proposed, in which both low-level features and high-level image semantics extracted from each color image are employed. To extract high-level image semantics from each color image, the visual attention saliency map for each color image is generated by three (color, intensity, and orientation) feature maps, which is used to guide region merging using “simple” modified PSO and a hybrid fitness function for color image segmentation. The proposed approach contains four stages, namely, color quantization, feature extraction, small region elimination, and region merging using “simple” modified PSO. Based on the experimental results obtained in this study, as compared with four comparison approaches, the proposed approach usually provides the better color image segmentation results.