Please wait a minute...
J4  2013, Vol. 47 Issue (3): 422-430    DOI: 10.3785/j.issn.1008-973X.2013.03.005
计算机技术     
基于Gabor滤波器的全参考图像质量评价方法
王翔1,2,丁勇1
1. 浙江大学 超大规模集成电路设计研究所, 浙江 杭州 310027;
2. 杭州电子科技大学 射频电路与系统教育部重点实验室, 浙江 杭州 310018
Full reference image quality assessment based on Gabor filter
WANG Xiang1, 2, DING Yong1
1. Institute of VLSI Design, Zhejiang University, Hangzhou 310027, China;2. Key Laboratory of Radio Frequency
Circuits and Systems of Ministry of Education, Hangzhou Dianzi University, Hangzhou 310018, China
 全文: PDF  HTML
摘要:

针对现有图像质量评价方法无法像人眼一样准确地评价各种图像失真,提出一种基于Gabor滤波器的全参考型图像质量评价方法.Gabor滤波器采用复数波形去调制高斯函数,得到一个在时间和频域上联合分辨率达到理论极限.通过优化Gabor滤波器的参数,可以有效地模拟人眼视觉特性.使用Gabor滤波器对图像的特征信息进行提取和对比之后,可以得到较好的图像质量评价效果.实验结果表明:该方法在对各种典型的失真图像的质量评价中,客观评分的各项指标均与人的主观感受较为一致.

Abstract:

To resolve the problem that existing image quality assessment methods cannot assess the images as accurate as human visual systems, a full reference image quality assessment method based on Gabor filter was proposed. Gabor filter uses complex waveforms to modulate Gaussian function. It can simultaneously reach the theoretically limited lower bound in time and frequency on the product of its bandwidth and duration. The parameters of Gabor filter are optimized to simulate the human visual system  effectively. After extracting the features from the Gabor filter and comparing them, better effects of image quality assessment are achieved. Experimental results show that the proposed method can correlate well with the human subjectivity in all kinds of distortions listed in the reference database.

出版日期: 2013-03-01
:  TP 391  
基金资助:

国家”863”高技术研究发展计划资助项目(2009AA011706);浙江大学基本科研业务费专项资金资助项目(KYJD09012).

通讯作者: 丁勇,男,副教授.     E-mail: dingy@vlsi.zju.edu.cn
作者简介: 王翔,(1984-),男,讲师,从事数字图像处理、数字视频SoC研究.E-mail:wangxiang@hdu.edu.cn
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  

引用本文:

王翔,丁勇. 基于Gabor滤波器的全参考图像质量评价方法[J]. J4, 2013, 47(3): 422-430.

WANG Xiang, DING Yong. Full reference image quality assessment based on Gabor filter. J4, 2013, 47(3): 422-430.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2013.03.005        http://www.zjujournals.com/eng/CN/Y2013/V47/I3/422

[1] WANG Z, BOVIK A C. Modern image quality assessment [M]. San Rafael, CA: Morgan & Claypool, 2006.
[2] 王翔. 数字图像缩放及图像质量评价关键技术研究 [D]. 杭州: 浙江大学, 2012: 75-92.
WANG Xiang. Research on image scaling and image quality assessment [D]. Hangzhou: Zhejiang University, 2012: 75-92.
[3] VQEG. Final report from the video quality experts group on the validation of objective models of video quality assessment [EB/OL]. [20000305]. http :// www. vqeg. org/.
[4] MIYAHARA M, KOTANI K, ALGAZI V R. Objective picture quality scale (PQS) for image coding [J]. IEEE Transactions on Communications, 1998, 46(9): 1215-1225.
[5] WANG Z, BOVIK A C. A universal image quality index [J]. IEEE, Signal Processing Letters, 2002, 9(3): 81-84.
[6] WANG Z, BOVIK A C, SHEIKH H R, et al. Image quality assessment: from error visibility to structural similarity [J]. IEEE Transactions on Image Processing, 2004, 13(4): 600612.
[7] WANG Z, SIMONCELLI E P, BOVIK A C. Multiscale structural similarity for image quality assessment [C]∥ Proceedings of the 37th IEEE Asilomar Conference on Signals, Systems and Computers. California: IEEE, 2003: 1398-1402.
[8] RAO D V, REDDY L P. Contrast weighted perceptual structural similarity index for image quality assessment [J]. Journal of Electronic Imaging, 2010, 19(1): 0110031-9.
[9] LAM E P, LOO K C. An image similarity measure using homogeneity regions and structure[C]∥ Proceedings of SPIE, Image Quality and System Performance V. 2008, 6808: 680-711.
[10] SHEIKH H R, BOVIK A C, VECIANA G DE. An information fidelity criterion for image quality assessment using natural scene statistics [J]. IEEE Transactions on Image Processing, 2005, 14(12): 2117-2128.
[11] TAO D, LI X, LU W, et al. Reducedreference IQA in contourlet domain[J]. IEEE Transactions on Systems, Man, and Cybernetics  Part B: Cybernetics, 2009, 39(6): 1623-1627.
[12] LI Q, WANG Z. Reducedreference image quality assessment using divisive normalizationbased image representation [J]. IEEE Journal of Selected Topics in Signal Processing, 2009, 3(2): 202-211.
[13] FERZLI R, KARAM L J. A noreference objective image sharpness metric based on the notion of just noticeable blur (JNB) [J]. IEEE Transactions on Image Processing, 2009, 18(4): 717-728.
[14] SHEIKH H R, BOVIK A C, CORMACK L. Noreference quality assessment using natural scene statistics: JPEG2000[J]. IEEE Transactions on Image Processing, 2005, 14(11): 1918-1927.
[15] ECKERT M P, BRADLEY A P. Perceptual quality metrics applied to still image compression [J]. Signal Processing Special Issue on Image and Video Quality Metric, 1998, 70: 177-200.
[16] DAUGMAN J G. Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by twodimensional visual cortical filters [J]. Journal of the Optical Society of America A Optics and Image Science, 1985(2): 1160-1169.
[17] DE VALOIS R L, ALBRECHT D G, THORELL L G. The orientation and direction selectivity of cells in macaque visual cortex [J]. Vision Research, 1982, 22: 531-544.
[18] WANG Z, SIMONCELLI E P. Translation insensitive image similarity in complex wavelet domain [C]∥ IEEE International Conference on Acoustics, Speech & Signal Processing. Philadelphia: IEEE, 2005:573-576.
[19] BROOKS A C, ZHAO X N, PAPPAS T N. Structural similarity quality metrics in a coding context: exploring the space of realistic distortions[J]. IEEE Transactions on Image Processing, 2008, 17(8): 1261-1273.
[20] SHEIKH H R, WANG Z, CORMACK L, et al. LIVE image quality assessment database release 2[EB/OL]. [20111114]. http:∥live.ece.utexas.edu/research/quality.
[21] SARNOFF CORPORATION. JNDmetrix Technology [EB/OL]. [2011-12-05]. http :∥www. sarnoff. com/ products services/ video vision/ jndmetrix/ downloads. asp.

[1] 赵建军,王毅,杨利斌. 基于时间序列预测的威胁估计方法[J]. J4, 2014, 48(3): 398-403.
[2] 崔光茫, 赵巨峰, 冯华君, 徐之海, 李奇, 陈跃庭. 非均匀介质退化图像快速仿真模型的建立[J]. J4, 2014, 48(2): 303-311.
[3] 张天煜, 冯华君, 徐之海, 李奇, 陈跃庭. 基于强边缘宽度直方图的图像清晰度指标[J]. J4, 2014, 48(2): 312-320.
[4] 刘中, 陈伟海, 吴星明, 邹宇华, 王建华. 基于双目视觉的显著性区域检测[J]. J4, 2014, 48(2): 354-359.
[5] 王相兵,童水光,钟崴,张健. 基于可拓重用的液压挖掘机结构性能方案设计[J]. J4, 2013, 47(11): 1992-2002.
[6] 王进, 陆国栋, 张云龙. 基于数量化一类分析的IGA算法及应用[J]. J4, 2013, 47(10): 1697-1704.
[7] 刘羽, 王国瑾. 以已知曲线为渐进线的可展曲面束的设计[J]. J4, 2013, 47(7): 1246-1252.
[8] 胡根生,鲍文霞,梁栋,张为. 基于SVR和贝叶斯方法的全色与多光谱图像融合[J]. J4, 2013, 47(7): 1258-1266.
[9] 吴金亮, 黄海斌, 刘利刚. 保持纹理细节的无缝图像合成[J]. J4, 2013, 47(6): 951-956.
[10] 朱凡,李悦,蒋 凯,叶树明,郑筱祥. 基于偏最小二乘的大鼠初级运动皮层解码[J]. J4, 2013, 47(5): 901-905.
[11] 陈潇红,王维东. 基于时空联合滤波的高清视频降噪算法[J]. J4, 2013, 47(5): 853-859.
[12] 吴宁, 陈秋晓, 周玲, 万丽. 遥感影像矢量化图形的多层次优化方法[J]. J4, 2013, 47(4): 581-587.
[13] 计瑜,沈继忠,施锦河. 一种基于盲源分离的眼电伪迹自动去除方法[J]. J4, 2013, 47(3): 415-421.
[14] 童水光, 王相兵, 钟崴, 张健. 基于BP-HGA的起重机刚性支腿动态优化设计[J]. J4, 2013, 47(1): 122-130.
[15] 刘芳, 孙芸, 杨庚, 林海. 基于粒子群优化算法的社交网络可视化[J]. J4, 2013, 47(1): 37-43.