基于人眼视觉特性的彩色图像质量评价

图像处理系统的性能优劣的评判往往需要一个合理迅速的图像质量评价算法作为支撑.传统的图像质量评价算法由于没有充分考虑人眼的视觉特性,使得质量评价结果与实际图像的人眼感知质量不符.根据人眼对图像边缘信息非常敏感这一人眼视觉特性,提出一种综合图像边缘和背录相似度的算法(EBS)来评价彩色图像质量,即通过比较失真彩色图像与原始参考图像的边缘以及除边缘之外的背景相似程度最终确定失真图像的质量.应用于由779幅包含五种类型失真的图像质量评价库的实验结果表明,该算法的评价结果相比PSNR,MSSIM,IFC以及基于像素域的VIF等算法与图像的主观评价结果(由DMOS值表示--将背景不同的一组观察者对失真图像的评分进行统计平均后所得到的评价结果)更一致,也即该算法的评价结果更接近图像的实际视觉感知质量.     

一种基于HWD的图像质量评价测度

提出了一种新的图像质量评价测度.首先对图像进行Hybrid Wavelets and Directional Filter Banks (HWD)分解,得到相应的尺度和方向子带信息.然后对各个子带进行对比敏感度掩模,使不同尺度和方向子带的信息具有相同的灵敏度.根据人类视觉感知特性设定视觉感知阈值,获得相应的视觉感知系数并归一化.利用参考图像和失真图像视觉感知系数差值的变化得到相应的图像质量评价测度.实验结果表明本测度与主观感知有很好的一致性,能准确地反映人眼对图像的视觉感知.     

一种基于WBCT的自然图像质量评价方法

部分参考型图像质量评价的性能依赖于图像的特征提取和稀疏表示.WBCT(Wavelet-based Contourlet Transform)是一种无冗余度的图像稀疏表示方法,能有效地反映图像的视觉感知特性,可以用来捕捉由于图像失真而引起的视觉感知的变化.为此,结合部分参考型图像质量评价模型和WBCT,提出了一种自然图像质量客观评价方法.实验结果表明,利用该方法所得到的图像质量客观评价结果与主观评价结果之间具有很好的一致性,能准确地反映人眼对图像质量的主观感受.     

基于多尺度边缘结构相似性的图像质量评价

基于结构相似度(SSIM)的图像质量评价方法是从视觉区域提取图像的结构性信息,但在评价模糊较严重的图像时存在其局限性,因此本文将图像边缘和SSIM相结合,提出了基于多尺度边缘结构相似度(MESS)的图像质量评价方法。实验结果表明,由于MESS考虑了边缘信息对于人眼感知结构信息的重要性,评价结果比SSIM更加符合人眼视觉感知特性。     

一种基于最小可察觉失真的立体图像质量客观评价方法

立体图像质量是评价立体视频系统性能的有效途径,而如何利用人类视觉特性对立体图像质量进行有效的评价是目前的研究难点。本文通过分析最小可察觉失真(JND,just noticeable distortion)视觉感知模型,并结合反映图像结构信息的奇异值矢量,提出了一种基于JND的立体图像质量客观评价方法。评价方法由图像质量评价和深度感知评价两部分组成,首先提取反映图像质量和深度感知的特征信息作为立体图像特征信息,然后根据立体图像的不同失真类型情况对其特征进行融合,通过支持向量回归(SVR,support vector Regression)预测得出立体图像质量的客观评价值。实验结果表明,采用本文提出的客观评价方法对立体数据测试库进行评价,在不同失真类型或混合失真评价结果中,Pearson线性相关系数(CC)值均在0.94以上,Spearman等级相关系数(SROCC)值均在0.92以上,符合人眼视觉特性,能够很好地预测人眼对立体图像的主观感知。     

夜视融合图像质量主观评价方法

为建立通用、客观的融合图像质量评价方法,在分析图像质量主观评价方法基础上,研究了融合图像质量主观评价对象、评价条件、评价指标和数据处理等关键环节,结合目标探测识别与场景理解两个典型的视觉任务,提出了目标可探测性和细节可分辨性两个主观评价指标,并研究了图像整体感知质量与这两个指标的相关性。对3种不同场景的微光与红外融合图像,采用9种融合方法获得的189幅融合图像的统计分析结果显示,细节可分辨性和图像整体感知质量相关性好,而目标可探测性虽然和图像整体感知质量相关性较差,但在基于具体视觉任务的融合图像质量评价过程中,仍可作为有效评价指标之一。     

基于波前像差的图像质量评价方法研究

图像质量评价的研究已成为图像信息工程的基础技术之一。由于图像的最终接受者是人,所以评价图像质量应反映出人类的主观视觉感知。为构造一种符合人眼视觉特性的图像质量评价方法,利用点扩散函数针对人眼建立了含有波前像差信息的图像视觉评价模型,并用此模型分别对添加不同噪声的图像进行图像质量评价。实验结果表明,该方法是可行的、有效的,不同的人眼对同一幅图像的评价存在有差异,人眼波前像差越小观察到的图像越清晰。该方法不仅能够在评价图像质量时准确反映人眼的主观感知,而且能够直观地呈现不同人眼实际看到的图像。     

帧频和响应时间对移动显示LCD图像质量的影响

应用视觉感知实验的方法对移动显示(手机)用LCD的运动图像质量进行了主观评价,研究了帧频、响应时间和视频图像内容对运动图像质量的影响.通过对实验数据的统计分析,发现三者对视觉感知的运动图像质量均有统计学意义的影响.帧频较高的运动图像质量较好,且存在一个最优的频帧;响应时间较长的运动图像质量较差;而视频图像内容不同,被感知的运动伪像也不同,模糊和跳跃是最容易被感知的运动图像失真.     

基于参数估计的无参考型图像质量评价算法

针对现有客观图像质量评价算法通用性差及人类主观感知相关性弱等问题,该文提出一种基于参数估计的无参考型图像质量评价算法。该算法通过分析图像本身所蕴含的质量特征,提取出图像结构信息、颜色信息和视觉信息的评价度量指标,采用回归分析的方法估计出相应指标的参数。实验结果表明,该算法与主观评价结果一致性好、鲁棒性强,优于其它客观评价算法,能够准确反映人类对图像质量的视觉感知效果。     

基于奇异值分解与自然图像统计的无参考图像质量评价方法

针对图像质量评价问题,从自然图像统计与SVD角度出发,提出一种通用无参考图像质量评价方法.方法对待测失真图像进行局部归一化,利用奇异值分解提取图像高频信息,采用非对称广义高斯分布进行模拟高频信息的自然图像统计特征,构建图像质量特征向量;利用支持向量机构建图像质量回归模型,实现图像质量评价.通过在LIVE2图像质量评价数...     

航空图像质量判别技术

航空摄影是遥感和军事侦察的主要信息源,航空图像质量的好坏直接决定着所获取信息的充分性和准确性。随着图像质量判别技术在图像处理领域的广泛应用,航空图像质量判别技术也引起了广泛的关注。本文首先提出影响图像质量的主要因素,并简要阐述了目前航空及其它相关领域常用的图像质量判别方法,最后介绍了人眼的视觉生理和心理特性,指出将人眼视觉特性(HVS)引入图像质量判别的发展趋势。     

Statistical Study of Edges in TV Pictures

The present study is devoted to the statistical analysis of edges in still monochrome TV pictures. The visual information carried by the edges is especially important both for image interpretation and for subjective image quality evaluation. Statistical knowledge on edges is helpful to improve image coding techniques significantly as well as processing techniques for scene analysis. After an introduction on nonstationary local statistical models, we describe the parameters of edges and the methods used to measure them. Statistical data collected on these parameters are then presented. The data concern orientation, edge length, edge width, runlength between edges and edge slope probability distributions as well as the measure of orientation continuity along an edge and the relative frequencies of edge pixels and contrasted isolated pixels.     

基于结构相似的小波域图像质量评价方法的研究

 小波域的图像处理已经成为图像处理领域的重要组成部分,研究能嵌入在小波域图像处理算法中的图像质量评判方法显得至关重要.空间域结构相似度SSIM具有计算简单、与主观评分相关性高等优点.本文通过对小波域图像结构特性的研究,提出了小波域结构相似度(DWTSSIM)的图像质量评价方法.实验结果表明DWTSSIM比SSIM更加符合人眼的视觉特性,可以更好地评判图像质量,并且能容易地嵌入在小波域图像处理算法中,在图像处理过程中指导或调节算法.     

Quantitative evaluation of enhancement techniques

Enhancement techniques are often used in image processing. In this paper, a quantitative measure of the image quality through evaluation of the coefficient of information content and the entropy has been suggested to evaluate the effect of enhancement. The image has been assumed to be a sample function of a homogeneous random field and the pixel values are estimated from the ‘past’ pixel values. The difference between the estimated value and the actual value of the pixel has been used as the criterion for defining the coefficient of information content. Also, the entropy obtained using the co-occurrance matrix of the image, has been used as a quantitative measure of the image quality. Measurements of the image quality through the evaluation of the coefficient of information content and the entropy have been carried out for the test images and the results of these measurements have been presented.     

Image information and visual quality.

Measurement of visual quality is of fundamental importance to numerous image and video processing applications. The goal of quality assessment (QA) research is to design algorithms that can automatically assess the quality of images or videos in a perceptually consistent manner. Image QA algorithms generally interpret image quality as fidelity or similarity with a "reference" or "perfect" image in some perceptual space. Such "full-reference" QA methods attempt to achieve consistency in quality prediction by modeling salient physiological and psychovisual features of the human visual system (HVS), or by signal fidelity measures. In this paper, we approach the image QA problem as an information fidelity problem. Specifically, we propose to quantify the loss of image information to the distortion process and explore the relationship between image information and visual quality. QA systems are invariably involved with judging the visual quality of "natural" images and videos that are meant for "human consumption." Researchers have developed sophisticated models to capture the statistics of such natural signals. Using these models, we previously presented an information fidelity criterion for image QA that related image quality with the amount of information shared between a reference and a distorted image. In this paper, we propose an image information measure that quantifies the information that is present in the reference image and how much of this reference information can be extracted from the distorted image. Combining these two quantities, we propose a visual information fidelity measure for image QA. We validate the performance of our algorithm with an extensive subjective study involving 779 images and show that our method outperforms recent state-of-the-art image QA algorithms by a sizeable margin in our simulations. The code and the data from the subjective study are available at the LIVE website.     

基于应用的可见光遥感图像质量评价方法研究

遥感应用需求的增加和应用水平的提高,对遥感图像质量提出越来越高的要求。为提高图像质量,一方面不断改进成像系统,另一方面也研究开发出各种图像处理方法,其中如何评价图像处理前后图像质量的变化是处理算法开发的重要环节。从应用的角度,通过对比评价图像处理前后的质量,初步研究提出了基于图像应用的主、客观评价方法,以找出算法处理的薄弱环节,为算法的优化提供支持。     

A method of image quality assessment for compressive sampling video transmission

Based on compressive sampling transmission model, we demonstrate here a method of quality evaluation for the reconstruction images, which is promising for the transmission of unstructured signal with reduced dimension. By this method, the auxiliary information of the recovery image quality is obtained as a feedback to control number of measurements from compressive sampling video stream. Therefore, the number of measurements can be easily derived at the condition of the absence of information sparsity, and the recovery image quality is effectively improved. Theoretical and experimental results show that this algorithm can estimate the quality of images effectively and is in well consistency with the traditional objective evaluation algorithm.     

基于DWT-SVD的彩色图像水印算法

本文根据奇异值分解理论把灰度水印嵌入到彩色图像的DWT分量中。为了既能保证算法的鲁棒性,又能够尽可能地提高不可见性,先将原图像分为RGB三个分量,将水印的信息添加到了RGB空间的B分量上,实验证明水印嵌入到蓝色分量比嵌入到其他颜色分量中可以更好地保持原始图像的感知质量。本文在提取水印时设定了阈值,如果奇异值分解对角线上的值低于这个阈值,就会用上面一行的值代替对角线上的值。实验证明,该方案对JPEG压缩和中值滤波等处理具有较好的鲁棒性。     

Identification of bitmap compression history: JPEG detection and quantizer estimation

Sometimes image processing units inherit images in raster bitmap format only, so that processing is to be carried without knowledge of past operations that may compromise image quality (e.g., compression). To carry further processing, it is useful to not only know whether the image has been previously JPEG compressed, but to learn what quantization table was used. This is the case, for example, if one wants to remove JPEG artifacts or for JPEG re-compression. In this paper, a fast and efficient method is provided to determine whether an image has been previously JPEG compressed. After detecting a compression signature, we estimate compression parameters. Specifically, we developed a method for the maximum likelihood estimation of JPEG quantization steps. The quantizer estimation method is very robust so that only sporadically an estimated quantizer step size is off, and when so, it is by one value.