激光与光电子学进展, 2017, 54 (7): 071001, 网络出版: 2017-07-05   

基于高阶相位一致性的混合失真图像质量评价 下载: 634次

Multiply-Distorted Image Quality Assessment Based on High-Order Phase Congruency
作者单位
天津大学电气自动化与信息工程学院, 天津 300072
引用该论文

侯春萍, 马彤彤, 岳广辉, 冯丹丹, 刘月. 基于高阶相位一致性的混合失真图像质量评价[J]. 激光与光电子学进展, 2017, 54(7): 071001.

Hou Chunping, Ma Tongtong, Yue Guanghui, Feng Dandan, Liu Yue. Multiply-Distorted Image Quality Assessment Based on High-Order Phase Congruency[J]. Laser & Optoelectronics Progress, 2017, 54(7): 071001.

参考文献

[1] 薛小波, 郁 梅, 何美伶. 基于仿视觉细胞模型的立体图像质量评价方法[J]. 激光与光电子学进展, 2016, 53(4): 041004.

    Xue Xiaobo, Yu Mei, He Meiling. Stereoscopic image-quality-assessment method based on visual cell model[J]. Laser & Optoelectronics Progress, 2016, 53(4): 041004.

[2] Gu K, Zhai G, Liu M, et al. FISBLIM: a five-step blind metric for quality assessment of multiply distorted images[C]. 2013 IEEE Workshop on Signal Processing Systems (SiPS), 2013: 241-246.

[3] Gu K, Zhai G, Yang X, et al. Hybrid no-reference quality metric for singly and multiply distorted images[J]. IEEE Transactions on Broadcasting, 2014, 60(3): 555-567.

[4] Li Q, Lin W, Fang Y. No-reference quality assessment for multiply-distorted images in gradient domain[J]. IEEE Signal Processing Letters, 2016, 23(4): 541-545.

[5] 李澄非, 陈新华. 融合局部二值模式和Hu矩特征的车型识别[J]. 激光与光电子学进展, 2016, 53(10): 101503.

    Li Chengfei, Chen Xinhua. Vehicle type recognition based on combining local binary pattern and Hu matrix feature[J]. Laser & Optoelectronics Progress, 2016, 53(10): 101503.

[6] Ghosh K, Sarkar S, Bhaumik K. Understanding image structure from a new multi-scale representation of higher order derivative filters[J]. Image and Vision Computing, 2007, 25(8): 1228-1238.

[7] 苑玮琦, 范永刚, 柯 丽. 相位一致性和对数Gabor滤波器相结合的掌纹识别方法[J]. 光学学报, 2010, 30(1): 147-152.

    Yuan Weiqi, Fan Yonggang, Ke Li. Palmprints recognition method based on the phase consistency combined with log-gabor filter[J]. Acta Optica Sinica, 2010, 30(1): 147-152.

[8] Kovesi P. Phase congruency detects corners and edges[C]. The Australian Pattern Recognition Society Conference: DICTA, 2003: 309-318.

[9] Gu K, Zhai G, Yang X, et al. A new reduced-reference image quality assessment using structural degradation model[C]. 2013 IEEE International Symposium on Circuits and Systems (ISCAS), IEEE, 2013: 1095-1098.

[10] Jayaraman D, Mittal A, Moorthy A K, et al. Objective quality assessment of multiply distorted images[C]. Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), 2012, 43(4): 1693-1697.

[11] Haralick R M, Shanmugam K. Textural features for image classification[J]. IEEE Transactions on Systems, Man & Cybernetics, 1973, 3(6): 610-621.

[12] 李 梦, 华玮平, 赵巨峰. 使用多尺度视觉注意提取的双波段图像融合[J]. 激光与光电子学进展, 2015, 52(12): 121002.

    Li Meng, Hua Weiping, Zhao Jufeng. Dual-band image fusion using visual attention extraction with multiple windows[J]. Laser & Optoelectronics Progress, 2015, 52(12): 121002.

[13] 赵树森, 陈思嘉, 沈京玲. 用支持向量机识别毒品的太赫兹吸收光谱[J]. 中国激光, 2009, 36(3): 752-757.

    Zhao Shusen, Chen Sijia, Shen Jingling. Identification of terahertz absorption spectra of illicit drugs using support vector machines[J]. Chinese J Lasers, 2009, 36(3): 752-757.

[14] 陈 静, 江 灏, 刘暾东, 等. 基于最小二乘支持向量回归模型的拉曼光纤放大器优化设计[J]. 光学学报, 2015, 35(11): 1123004.

    Chen Jing, Jiang Hao, Liu Tundong, et al. Optimization for raman fiber amplifiers based on least squares support vector regression model[J]. Acta Optica Sinica, 2015, 35(11): 1123004.

[15] 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): 600-612.

[16] Larson E C, Chandler D M. Most apparent distortion: full-reference image quality assessment and the role of strategy[J]. Journal of Electronic Imaging, 2010, 19(1): 011006.

[17] Zhang L, Zhang L, Mou X, et al. FSIM: a feature similarity index for image quality assessment[J]. IEEE Transactions on Image Processing, 2011, 20(8): 2378-2386.

[18] Xue W, Zhang L, Mou X, et al. Gradient magnitude similarity deviation: a highly efficient perceptual image quality index[J]. IEEE Transactions on Image Processing, 2014, 23(2): 684-695.

[19] Mittal A, Moorthy A K, Bovik A C. No-reference image quality assessment in the spatial domain[J]. IEEE Transactions on Image Processing, 2012, 21(12): 4695-4708.

[20] Zhang L, Zhang L, Bovik A C. A feature-enriched completely blind image quality evaluator[J]. IEEE Transactions on Image Processing, 2015, 24(8): 2579-2591.

[21] Xue W, Mou X, Zhang L, et al. Blind image quality assessment using joint statistics of gradient magnitude and Laplacian features[J]. IEEE Transactions on Image Processing, 2014, 23(11): 4850-4862.

侯春萍, 马彤彤, 岳广辉, 冯丹丹, 刘月. 基于高阶相位一致性的混合失真图像质量评价[J]. 激光与光电子学进展, 2017, 54(7): 071001. Hou Chunping, Ma Tongtong, Yue Guanghui, Feng Dandan, Liu Yue. Multiply-Distorted Image Quality Assessment Based on High-Order Phase Congruency[J]. Laser & Optoelectronics Progress, 2017, 54(7): 071001.

本文已被 9 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!