[1] 马骕, 邓喀中, 庄会富, 等. 中低分辨率SAR纹理多特征的Otsu变化检测[J]. 激光与光电子学进展, 2017, 54(6): 062804.

    马骕, 邓喀中, 庄会富, 等. 中低分辨率SAR纹理多特征的Otsu变化检测[J]. 激光与光电子学进展, 2017, 54(6): 062804.

    Ma Su, Deng Kazhong, Zhuang Huifu, et al. Otsu change detection of low and moderate resolution synthetic aperture radar image by using multi-texture features[J]. Laser & Optoelectronics Progress, 2017, 54(6): 062804.

    Ma Su, Deng Kazhong, Zhuang Huifu, et al. Otsu change detection of low and moderate resolution synthetic aperture radar image by using multi-texture features[J]. Laser & Optoelectronics Progress, 2017, 54(6): 062804.

[2] 康乐, 张群, 李涛泳, 等. 基于贝叶斯学习的下视三维合成孔径雷达成像方法[J]. 光学学报, 2017, 37(6): 0611003.

    康乐, 张群, 李涛泳, 等. 基于贝叶斯学习的下视三维合成孔径雷达成像方法[J]. 光学学报, 2017, 37(6): 0611003.

    Kang Le, Zhang Qun, Li Taoyong, et al. Imaging method of downward-looking three dimensional synthetic aperture radar based on Bayesian learning[J]. Acta Optica Sinica, 2017, 37(6): 0611003.

    Kang Le, Zhang Qun, Li Taoyong, et al. Imaging method of downward-looking three dimensional synthetic aperture radar based on Bayesian learning[J]. Acta Optica Sinica, 2017, 37(6): 0611003.

[3] Lowe D G. Distinctive image features from scale-invariant keypoints[J]. Computer Vision, 2004, 60(2): 91-110.

    Lowe D G. Distinctive image features from scale-invariant keypoints[J]. Computer Vision, 2004, 60(2): 91-110.

[4] Wang Z, Wu F, Hu Z. MSLD: a robust descriptor for line matching[J]. Pattern Recognition, 2009, 42(5): 941-953.

    Wang Z, Wu F, Hu Z. MSLD: a robust descriptor for line matching[J]. Pattern Recognition, 2009, 42(5): 941-953.

[5] 周海洋, 朱鑫炎, 余飞鸿. 改进型高效三角形相似法及其在深空图像配准中的应用[J]. 光学学报, 2017, 37(4): 0410003.

    周海洋, 朱鑫炎, 余飞鸿. 改进型高效三角形相似法及其在深空图像配准中的应用[J]. 光学学报, 2017, 37(4): 0410003.

    Zhou Haiyang, Zhu Xinyan, Yu Feihong. Improved efficient triangle similarity algorithm for deep-sky image registration[J]. Acta Optica Sinica, 2017, 37(4): 0410003.

    Zhou Haiyang, Zhu Xinyan, Yu Feihong. Improved efficient triangle similarity algorithm for deep-sky image registration[J]. Acta Optica Sinica, 2017, 37(4): 0410003.

[6] Margerida S, Sandra H. Separation between water and land in SAR images using region-based level sets[J]. IEEE Geoscience and Remote Sensing Letters, 2009, 6(3): 471-475.

    Margerida S, Sandra H. Separation between water and land in SAR images using region-based level sets[J]. IEEE Geoscience and Remote Sensing Letters, 2009, 6(3): 471-475.

[7] Li SZ. Markov random field modeling in image analysis[M]. New York: Springer-Verlag, 2009.

    Li SZ. Markov random field modeling in image analysis[M]. New York: Springer-Verlag, 2009.

[8] Anthony P D. An automatic U-distribution and Markov random field segmentation algorithm for PolSAR images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(4): 1819-1827.

    Anthony P D. An automatic U-distribution and Markov random field segmentation algorithm for PolSAR images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(4): 1819-1827.

[9] Huawu D, Clausi D A. Unsupervised segmentation of synthetic aperture radar sea ice imagery using a novel Markov random field model[J]. IEEE Transactions on Geoscience Remote Sensing, 2005, 43(3): 528-538.

    Huawu D, Clausi D A. Unsupervised segmentation of synthetic aperture radar sea ice imagery using a novel Markov random field model[J]. IEEE Transactions on Geoscience Remote Sensing, 2005, 43(3): 528-538.

[10] 贺飞跃, 田铮, 付辉敬, 等. 带边缘惩罚和自适应权马尔科夫随机场的合成孔径雷达图像快速分割[J]. 光学学报, 2013, 33(8): 0811004.

    贺飞跃, 田铮, 付辉敬, 等. 带边缘惩罚和自适应权马尔科夫随机场的合成孔径雷达图像快速分割[J]. 光学学报, 2013, 33(8): 0811004.

    He Feiyue, Tian Zheng, Fu Huijing, et al. Efficient segmentation of SAR images using Markov random field models with edge penalties and an adaptive weighting parameter[J]. Acta Optica Sinica, 2013, 33(8): 0811004.

    He Feiyue, Tian Zheng, Fu Huijing, et al. Efficient segmentation of SAR images using Markov random field models with edge penalties and an adaptive weighting parameter[J]. Acta Optica Sinica, 2013, 33(8): 0811004.

[11] Mokhtarian F, Suomela R. Robust image corner detection through curvature scale space[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998, 20(12): 1376-1381.

    Mokhtarian F, Suomela R. Robust image corner detection through curvature scale space[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998, 20(12): 1376-1381.

[12] Mohammad A, Li G J. An improved curvature scale-space corner detector and a robust corner matching approach for transformed image identification[J]. IEEE Transactions on Image Processing, 2008, 17(12): 2425-2441.

    Mohammad A, Li G J. An improved curvature scale-space corner detector and a robust corner matching approach for transformed image identification[J]. IEEE Transactions on Image Processing, 2008, 17(12): 2425-2441.

[13] Goshtasby AA. 2-D and 3-D image registration for medical, remote sensing, and industrial applications[M]. Wiley-Interscience, 2005.

    Goshtasby AA. 2-D and 3-D image registration for medical, remote sensing, and industrial applications[M]. Wiley-Interscience, 2005.

[14] Myronenko A, Song X. Point set registration: coherent drift[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 32(12): 2262-2275.

    Myronenko A, Song X. Point set registration: coherent drift[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 32(12): 2262-2275.

[15] Jian B, Vemuri B C. Robust point set registration using Gaussian mixture models[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(8): 1633-1645.

    Jian B, Vemuri B C. Robust point set registration using Gaussian mixture models[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(8): 1633-1645.

[16] Liu S L, Sun G, Niu Z D. Robust rigid coherent point drift algorithm based on outlier suppression and its application in image matching[J]. Journal of Applied Remote Sensing, 2015, 9(1): 095085.

    Liu S L, Sun G, Niu Z D. Robust rigid coherent point drift algorithm based on outlier suppression and its application in image matching[J]. Journal of Applied Remote Sensing, 2015, 9(1): 095085.

[17] Li B. Probabilistic model for robust affine and non-rigid point set matching[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017, 39(2): 371-384.

    Li B. Probabilistic model for robust affine and non-rigid point set matching[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017, 39(2): 371-384.

[18] Tao W B, Sun K. Robust point sets matching by fusing feature and spatial information using non-uniform Gaussian mixture models[J]. IEEE Transactions on Image Processing, 2015, 24(11): 3754-3767.

    Tao W B, Sun K. Robust point sets matching by fusing feature and spatial information using non-uniform Gaussian mixture models[J]. IEEE Transactions on Image Processing, 2015, 24(11): 3754-3767.

[19] 唐智, 周荫情, 李景文. InSAR数据处理中基于相关系数的配准方法[J]. 雷达科学与技术, 2004, 2(2): 108-114.

    唐智, 周荫情, 李景文. InSAR数据处理中基于相关系数的配准方法[J]. 雷达科学与技术, 2004, 2(2): 108-114.

    Tang Zhi, Zhou Yinqing, Li Jingwen. Co-registration method based on correlation coefficient in InSAR data processing[J]. Radar Science and Technology, 2004, 2(2): 108-114.

    Tang Zhi, Zhou Yinqing, Li Jingwen. Co-registration method based on correlation coefficient in InSAR data processing[J]. Radar Science and Technology, 2004, 2(2): 108-114.