综合利用目标区域颜色纹理特征的彩色图像检索

基于内容的图像检索是当前图像数据库领域的一个研究热点。文章提出了一种基于目标区域的多特征彩色图像检索算法。首先获取彩色图像HSI色彩空间的亮度分量灰度图像,再计算得到亮度分量灰度图像的二值边缘图像,并根据边缘图像的连通性提取彩色图像的目标区域。然后抽取目标区域的颜色特征和纹理特征,并分别对两个特征的相似距离进行归一化。最后综合利用这两个特征共同进行检索。实验结果表明,该文的算法具有良好的性能,在检索准确率上获得了较好的效果。     

对比度、颜色一致性和灰度像素保持的消色算法

目的 为了解决目前消色算法中不能同时保持原始图像的对比度,颜色一致性和灰度像素特征的问题,提出一种新的优化算法,最大限度地同时保留这些视觉特性。方法 为了保持原始图像的结构和局部对比度信息,用双高斯模型构建像素对之间的误差能量项;为了保持颜色一致性,采用局部线性嵌入模型构建能量项,确保原始图像中颜色一致的像素在结果图像中也拥有一样的灰度级;为了保持灰度像素特征,先标记出原始图像中的灰度像素,并强制规定这些像素的灰度值是已知的且在消色变换的过程中始终不变,然后用双高斯模型构建出灰度像素与其他像素之间的误差能量项。线性结合这3个能量项,得到目标能量函数,再通过迭代法求解出使总能量值达到最小的灰度值,从而得到了最终的消色结果。结果 实验结果表明,本文算法能够同时较好地保持原始图像中的对比度、颜色一致性和灰度像素特征。结论 本文算法基本符合人类对图像对比度变化的感知程度,而且能够很好地保持细节信息和全局结构,可应用于数字打印、模式识别等方面,具有很大的应用价值。     

基于彩色传递的红外与可见光图像融合方法

提出了一种基于小波分解和彩色传递理论的图像融合方法。在小波变换的基础上，采用一种融合方法对红外和可见光图像进行融合处理；基于色空间变换对灰度融合图像进行彩色传递，实现灰度到彩色图像的转变。实验表明彩色传递图像的色彩接近自然景物颜色，优于传统的假彩色方法，更有利于人眼对目标和环境的判断识别。     

A comparative study of preprocessing mismatch effects in color image based face recognition

Face color information can play an important role in face recognition (FR) and it can be used to considerably improve FR performance obtained using only grayscale images. The color-based FR methods involve a preprocessing step where a color image is converted into either a monochromatic image or an image having a different color representation. In practical FR systems, the recording or transmission format of the testing images may be arbitrary or inconsistent depending on the application (e.g., face images could consist of grayscale or color pixels either in compressed or uncompressed form). Further, a wide variety of grayscale and color conversions can be used in the preprocessing step. This could lead to a so-called preprocessing mismatch in color-based FR methods: the training and testing face images, generated after preprocessing, do not match in terms of their degree of compression or in terms of their grayscale or color representations. In contrast to grayscale-based FR, a practical color-based FR system has a higher chance of being confronted with a preprocessing mismatch. The aim of this paper is to present a comparative study that addresses the impact of a preprocessing mismatch on color-image based FR methods. We explore three different types of preprocessing mismatches, which practical color-based FR system are highly likely to encounter. In addition, comparative and extensive experiments have been carried out to analyze the effects of the preprocessing mismatches on an FR performance, using Color FRETET, CMU-PIE, AR, and SCface public face databases. The important conclusions drawn from our experiments include: (1) of all color-based FR methods under consideration, color-based FR using feature-level fusion is the most robust approach to preprocessing mismatches; (2) the preprocessing mismatch caused by the use of compressed color images can significantly deteriorate FR performance of color-based FR methods; (3) grayscale testing images can be critical for the feasibility of color-based FR using an input-level fusion; (4) the preprocessing mismatch in terms of grayscale representation has little effect on the FR performances of color-based FR methods.     

一种彩色图像灰度化的自适应全局映射方法

研究采用RGB颜色分量加权和的全局映射, 进行彩色到灰度的变换算法. 根据彩色像素在不同颜色分量的统计信息, 自动生成各颜色分量的灰度化权重, 同时结合主客观图像质量标准, 探索自适应的全局映射灰度化算法. 实验证明, 本文提出的新算法在多数测试图像上的灰度化效果与传统的灰度化算法效果相当, 但对具有主题色的彩色图像可以获得显著改善的灰度图像视觉效果.     

A new steganographic method for color and grayscale image hiding

In this paper, we present a steganographic method for embedding a color or a grayscale image in a true color image. Three types of secret images can be carried by the proposed method: hiding a color secret image, hiding a palette-based 256-color secret image, and hiding a grayscale image in a true color image. Secret data are protected by the conventional crypto system DES. We compare the image quality and hiding capacity of the proposed method with those of the scheme in Lin et al.’s scheme. According to the experimental results, the image quality of the proposed method is better than that of the Lin et al.’s scheme. In addition, annotation data can be hidden with the secret image in the host image. The hiding capacity of the proposed method is greater than that of other compared schemes. The experimental results show that the proposed method is a secure steganographic method that provides high hiding capacity and good image quality.     

基于彩色图像四元数表示的彩色人脸识别

为了更有效地利用彩色人脸的色彩信息进行识别,提出了一种新的基于彩色图像四元数表示的算法. 首先基于彩色图像四元数表示和四元数代数理论定义了四元数伪Zernike矩(Quaternion pseudo-Zernike moments, QPZMs), 将传统的主要处理灰度图像的伪Zernike矩(Pseudo-Zernike moments, PZMs)推广应用于彩色图像,然后基于QPZMs构造了彩色人脸图像针对旋转、缩放和平移(Rotation, scaling, and translation, RST)变换的四元数值不变量,最后结合这些鲁棒的不变量特征和四元数BP神经网络(Quaternion back propagation neural network, QBPNN)分类器进行彩色人脸识别. 实验结果表明,与现有基于四元数的算法比较,本文算法在表情、光照、位置等变化方面具有更强的鲁棒性.     

基于YCbCr颜色空间的二维DCT彩色图像数字水印实用技术

作为版权保护的重要手段，数字水印技术已得到广泛的研究和应用，但是实用的彩色图像数字水印技术不多．特别是灰度级水印信号的嵌入算法不多．文中充分考虑到人类视觉系统特点，采用YCbCr彩色空间，将灰度图像水印信号嵌入栽体的亮度分量Y的DCT系数中．灰度图像的嵌入策略是采用整体DCT，排除DC系数和部分低频系数，而将水印信号嵌入栽体第100到100 N之间的中低频系数通道中．实验证明，该算法能够对剪切、旋转、翻转、比例缩放和平移等几何变换有较强的免疫力．同时对压缩、滤波和噪声污染等常见的信号处理也具有较强的免疫力。     

Perceptual Evaluation of Color‐to‐Grayscale Image Conversions

Color images often have to be converted to grayscale for reproduction, artistic purposes, or for subsequent processing. Methods performing the conversion of color images to grayscale aim to retain as much information about the original color image as possible, while simultaneously producing perceptually plausible grayscale results. Recently, many methods of conversion have been proposed, but their performance has not yet been assessed. Therefore, the strengths and weaknesses of color‐to‐grayscale conversions are not known. In this paper, we present the results of two subjective experiments in which a total of 24 color images were converted to grayscale using seven state‐of‐the‐art conversions and evaluated by 119 human subjects using a paired comparison paradigm. We surveyed nearly 20000 human responses and used them to evaluate the accuracy and preference of the color‐to‐grayscale conversions. To the best of our knowledge, the study presented in this paper is the first perceptual evaluation of color‐to‐grayscale conversions. Besides exposing the strengths and weaknesses of the researched methods, the aim of the study is to attain a deeper understanding of the examined field, which can accelerate the progress of color‐to‐grayscale conversion.     

基于p-Laplace方程的图像彩色化方法

灰度图像的彩色化是图像处理研究领域中富有挑战性的研究课题,且具有十分广阔的应用前景。在分析现有图像彩色化方法的基础上,提出了一种基于p-Laplace方程的图像彩色化新方法。新方法首先由用户在灰度图像上给定少量的颜色条带;然后通过求解p-Laplace方程实现颜色扩散的彩色化。由于p-Laplace算子是一个各向异性扩散的非线性算子,所以与采用偏微分方程方法的泊松方法和拉普拉斯方法相比,图像彩色化在扩展颜色的同时更能保持边缘效果。     

A new approach to morphological color image processing

This paper presents a new approach to the generalization of the concepts of grayscale morphology to color images. A new vector ordering scheme is proposed, infimum and supremum operators are defined, and the fundamental vector morphological operations are extracted. The basic properties of the presented vector morphology are described and its similarities to grayscale morphological operators are pointed out. The main advantages of the proposed methodology are that is vector preserving and provides improved results in many morphological applications. Furthermore, experimental results demonstrate the applicability of the proposed technique in a number of image processing and analysis problems, such as noise removal, edge detection and skeleton extraction.     

基于颜色编码和图像隐写术的可逆灰度方法

针对现有方法存在合成灰度图像视觉质量欠佳、重建彩色图像还原度不足的问题,提出一种基于颜色编码和图像隐写术的可逆灰度方法。其利用可逆神经网络构建更高效的颜色编解码器,并引入密集卷积块和通道注意力机制进一步提升网络模型的性能,综合减少编解码过程中的颜色信息丢失。之后,为使灰度图像负载编码信息以及减小嵌入过程导致的图像失真,设计了一种基于修改方向的图像隐写算法,通过自适应权值参数选择,以接近最优的方式满足不同的嵌入容量需求,减少对灰度图像的修改。在Kodak和McMaster数据集上的实验表明,与现有代表性可逆灰度方法相比较,该方法能够生成质量更高的可逆灰度图像以及重建更加还原的彩色图像,在图像可视化时具有更好的视觉效果,在标准参考图像的相似性评价指标方面也取得了更优的性能。     

New watermarking algorithm utilizing quaternion Fourier transform with advanced scrambling and secure encryption

Digital watermarking technology, as a powerful tool for copyright protection and content authentication of multimedia works, has received increasing attention, and the current image watermarking technology has developed significantly. Generally, embedding a watermark is done in grayscale images, mainly due to the fact that grayscale images are easier to process than color images, and grayscale images only contain brightness information and color-free information, in which an embedded watermark will not produce new color components. In real life, however, color images are more common than grayscale image information. To improve the security of the watermark information and the ability to embed the location and improve the security of the algorithm against a variety of attacks, this paper proposes an algorithm based on quaternion Fourier transform (QFT) with chaotic encryption and Arnold scrambling. Geometric Algebra (GA) can process color images in the form of vectors, and each component of Red,Green and Blue (RGB) should be processed separately. We utilized quaternion (which is a subalgebra of GA) and effectively completed color image processing by utilizing Fourier transform. After utilizing QFT, each component was made more secure by scrambling the pixels of the watermark and performing encryption utilizing chaotic sequencing. Different types of results utilizing Mean Square Error (MSE),Peak Signal to Noise Ratio (PSNR),Structure Similiarity Index Metric (SSIM), etc. were computed to verify the performance of our proposed algorithm and show that the robustness and security are high by utilizing our method.

     

Aliasing artifacts reduction with subband signal analysis for demosaicked images

Demosaicking is a process used to estimate missing color values from the subsampled color filter array (CFA) image to reduce the cost and volume of a digital still camera. However, by sampling theory, it is known that subsampling a signal causes overlaps of signals in the frequency domain, which is known as aliasing. Most current demosaicking processes cannot completely solve aliasing problem resulting in aliasing artifacts such as false colors and zipper effects. In this paper, we propose an algorithm to remove these aliasing artifacts in demosaicked color images. A luminance image with minimum aliasing is obtained from the CFA image by using a low-pass kernel with cutoff frequencies determined by an approximate model for the Fourier spectrum. An aliasing map is computed by analyzing subband signals of the CFA image based on the high correlation of the high-frequencies of the luminance and color channels. Then, a least squares of the luminance acquisition processes is used to design a cost function with the aliasing map to remove the aliasing artifacts. The experiments demonstrate that the proposed algorithm sufficiently removes aliasing artifacts and improves the quality of the color images.     

一种基于视觉感知的色彩量化算法

提出一种色彩量化算法.该算法将图像中的区域细分为边缘、内部平滑区域和内部纹理区域3个部分,并根据它们对视觉感知的重要程度赋予不同的量化权重,以达到强化视觉上相对重要的边缘和内部平滑区域、弱化视觉上相对不重要的复杂纹理区域的目的.另外,为了在量化效果和时间性能上取得折衷,对HSV色彩空间固定V值的蜂窝状分割量化算法进行改进,实现一种可在整个色彩空间完成动态分割的量化算法.在保证时间性能比原有算法略有改善的前提下,减少色彩量化的误差.实验结果表明,本文算法只需要为数较少的量化色彩就能达到较好的量化效果,特别适用于基于内容的图像检索等应用场合.     

基于改进C均值聚类的自适应图像分色算法

图像分色在纺织和印刷等行业中有着广泛而重要的应用,其目的是用尽量少的颜色来描述一幅真彩色图像,使得到的图像与原图像尽可能的接近。该文提出了一种基于改进C均值聚类的自适应图像分色算法。该算法首先随机产生一张颜色表,然后根据该颜色表对原图像的像素点进行聚类分析,产生初始分色图像。再根据C均值聚类的方法对初始聚类中心进行调整,生成新的分色图像,直到满足结束条件后结束算法。实验结果表明,该算法在大大减少原图像的颜色数量的同时基本保持分色图像的质量,是一种实用的分色方法。     

彩色图像分形维数的计算方法

分形维数是描述图像复杂性的一种重要测度,广泛应用于图像特征提取及图像分类、分割和检索等方面。多种黑白图像和灰度图像的分形维数计算方法已被提出,但其中很少有适用于彩色图像的分形维数计算方法。把计算灰度图像分形维数的差分盒维法扩展到欧氏五维空间,提出了一种简单且易实现的计算彩色图像分形维数的方法。实验结果表明,提出的方法能够捕捉到彩色图像纹理的复杂性,在识别彩色图像粗糙度变化和计算精度方面优于其它算法。     

融合颜色与光照信息的改进AKAZE图像匹配算法

传统AKAZE算法主要以图像的灰度信息作为输入,忽略了颜色与光照信息,且存在过多的冗余特征点。提出一种融合颜色与光照信息的改进图像匹配算法。在图像原始灰度信息中增加颜色补偿量和光照补偿量,克服传统AKAZE算法未利用颜色和光照信息来区分同名点的缺点。在特征点邻域内计算欧式距离和区域重复率以确定重叠程度较高的相邻特征点,比较相邻特征点的响应强度,将响应强度值较小的特征点作为冗余点并删除。在图像匹配后利用随机一致性算法剔除误匹配点对,通过并行运算对算法进行加速。实验结果表明,该算法可以有效识别同名点并剔除图像中的冗余点,运行效率优于SIFT和SURF等算法。     

基于融合策略的改进Retinex低照度图像增强算法

针对Retinex算法处理低照度彩色图像出现色彩失真,边缘保持性差等问题,提出一种基于融合策略的改进Retinex低照度图像增强算法;该算法首先在YIQ颜色空间提取亮度分量Y,对其进行MSR算法增强;然后采用高斯-拉普拉斯算子对彩色图像的RGB三个分量进行边缘检测,将其叠加合成后转换成灰度图;最后使用小波变换将两幅图像融合得到新的亮度分量,将其与I、Q分量融合后转回RGB颜色空间,从而获得色彩保真度高、细节清晰的图像;实验结果表明,该方法有效提高了图像边缘细节信息,避免了色彩失真,具有很好的视觉效果。     

基于高斯混合模型的色彩转换

在将彩色图像转变为黑白图像的应用中,传统的彩色一灰度转换方法无法有效地传递色彩差异反映的视觉信息,其时间开销太大或者需要人工交互,因此目前并没有得到实际推广应用.为了解决这些问题,提出一种基于多元高斯混合模型(GMM)的彩色一灰度转换算法.该算法从人眼对彩色图像的感知机制出发,把对彩色图像中的视觉信息提取过程视为多维数据的分类问题,首先通过重采样抽取训练数据点集,然后引入GMM对彩色图像中的像素分布进行建模,通过一个改进的Gibbs采样彩色图像建模算法取得模型参数,并实现高斯混合元数目的自动确定;最终实现彩色一灰度转换操作.实验证明,该算法能够较快地完成彩色一灰度的自动转换.并有效地保留了彩色图像中由色彩传递的视觉信息.