[1] HOU B, XU J, LIU F, et al.Image segmentation using se-cond generation bandelet-domain hidden Markov tree models［J］.Acta Automatica Sinica, 2009, 35(5)：498-504.
[2] XIANG H L, JIA J, JIAO L C.Image segmentation of self-organizing neural net works based on tree-type coefficients in Contourlet domain［J］.Systems Engineering and Electronic, 2008, 30(5)：843-846.
[3] CANDS E J.Monoscale ridgelets for the representation of images with edges ［R］.Technical report, Stanford Univ, 1999.
[4] CANDS E J, DONOHO D L.Curvelets［R］.Technical report, Stanford Univ, 1999.
[5] DOM N, VETTERLI M.Contourlets:A new directional multi-resolution image representation signals, systems and computers［C］//Conference Record of the Thirty-Sixth Asiloma Conference, Rochester, 2002:3-6.
[6] QIAN X H, GUO S X, LI X Y.Image understanding based global evaluation algorithm for segmentation［J］.Acta Electronic Sinica, 2012, 40(10):1975-1981.
[7] WANG J H, SUN W D.On the characteristics of Growing Cell Structures (GCS) neural network［J］.Neural Processing Letters (S1370-4621), 1999, 10(2):139-149.
[8] KINGSBURY N G.A dual-tree complex wavelet transform with improved orthogonality and symmetry properties［C］//Proceedings of International Conference on Image Processing, Vancouver, 2000:375-379.
[9] ANDERSON R, KINGSBURY N, FAUQUEUR J.Determining multiscale image feature angles from complex wavelet phases［C］//Proceedings of second International Conference on Image Analysis and Recognition, Toronto, 2005:490-498.
