\r曹清洁^{1, 2}，史再峰^{1, 3}，张嘉平¹，李杭原¹，高 静^{1, 3}，姚素英\r¹\r
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AuthorsHTML:\r曹清洁^{1, 2}，史再峰^{1, 3}，张嘉平¹，李杭原¹，高 静^{1, 3}，姚素英\r¹\r
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AuthorsListE:\rCao Qingjie^{1, 2}，Shi Zaifeng^{1, 3}，Zhang Jiaping¹，Li Hangyuan ¹，Gao Jing^{1, 3}，Yao Suying\r¹\r
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AuthorsHTMLE:\rCao Qingjie^{1, 2}，Shi Zaifeng^{1, 3}，Zhang Jiaping¹，Li Hangyuan ¹，Gao Jing^{1, 3}，Yao Suying\r¹\r
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Unit:\r\r1. 天津大学微电子学院，天津 300072；\r
\r\r2. 天津师范大学数学科学学院，天津 300387；
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\r3. 天津市成像与感知微电子技术重点实验室，天津 300072\r
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Unit_EngLish:\r1. School of Microelectronics，Tianjin University，Tianjin 300072，China；
2. School of Mathematical Sciences，Tianjin Normal University，Tianjin 300387，China；
3. Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology，Tianjin 300072，China\r
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Abstract_Chinese:\r图像质量评价在图像采集、图像压缩、图像传输等领域有着广泛的应用，一直是图像处理领域的研究热点之一．本文提出了一种模拟人的视觉感知过程中的对不同区域敏感度不同的特点，针对待评图像进行分区域采用不同标准的全参考型图像质量评价算法．该算法首先对图像颜色空间由RGB 转换到YIQ，使之更符合人类视觉特性；再对其亮度空间进行数学形态学的膨胀计算预处理，并用边缘检测算子标记出图像中所有的边缘像素点；根据5×5 的邻域内是否包含边缘点将图像分为纹理区和平滑区域．针对包含边缘特征的纹理区域的结构参数采用梯度进行描述，参考图像和失真图像在像素点的方差表述像素点失真的敏感性；对于平滑区域的像素点采用对比度作为表征结构信息的变量，并使用基于视觉显著性的综合策略；结合失真和参考图像的视觉显著性矩阵、结构相似性矩阵SCR(x)、色彩饱和度相似性矩阵，可分别得到纹理区和平滑区的图像质量评价分区域结果．取两个分区域结果的均值，可得到最后的全图像质量评价指标SMC-IQA．该算法在CSIQ、TID2008 和TID2013 等3 个通用的图像质量评价数据库上进行了实验．实验结果表明与主流的图像质量评测方法相比较，本文所提出的分区域多标准的全参考图像质量评价算法与主观评价的结果具有更好的一致性，更符合人类视觉系统的特性．\r
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Abstract_English:\rImage quality assessment is widely used in image collection，image compression，and image transmission. It is one of the research hotspots in image processing. This article proposes a full-reference image quality assessment algorithm，which simulates human visual perception with varying sensitivity to different regions. With this method，image color space was transformed from RGB to YIQ for consistency with the human visual system. A morphological dilation method was used during pretreatment，and all edge pixels were marked by edge detection operators. Thereafter，the image was segmented into texture region and smooth region according to whether or not the edge points were included in the 5×5 neighborhood. A gradient value was used to assess the structural parameters of the texture region. The variance in reference image and distorted image at a pixel level was used to assess pixel distortion. For pixels in the smooth region，the contrast value was used to assess the structure features，and a synthesis strategy based on visual salience was adopted. The image quality assessment results can be obtained by combining the visual saliency matrix，structure similarity matrix SCR(x)，and color saturation matrix of distortion and reference images. The final image quality assessment index(SMC-IQA)was the mean of the results from two kinds of regions. Experiments were conducted on the CSIQ，TID2008，and TID2013 databases. Compared with state-of-the-art image quality assessment methods，experiment results show that this algorithm is closer to subjective assessment index by the human visual system.\r
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Keyword_Chinese:全参考图像质量评价；分区域；形态学；边缘检测\r

Keywords_English:full-reference image quality assessment；sub-region；morphology；edge detection\r


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