Revision as of 21:44, 8 December 2014 edit Linking7 (talk \| contribs) 4 edits →1.Definition ← Previous edit		Revision as of 21:46, 8 December 2014 edit undo Linking7 (talk \| contribs) 4 edits add external resources Next edit →
Line 8: === 2.1 Discrete Wavelet Frame(DWF) === In order to do SCM we have to use discrete wavelet frame (DWF) transformation first to get a series of sub images. The discrete wavelet frames is nearly identical to the standard wavelet transform[3], except that one upsamples the filters, rather than downsamples the image. Given an image, the DWF decomposes its channel using the same method as the wavelet transform, but without the subsampling process. This results in four filtered images with the same size as the input image. The decomposition is then continued in the LL channels only as in the wavelet transform, but since the image is not subsampled, the filter has to be upsampled by inserting zeros in between its coefficients. The number of channels, hence the number of features for DWF is given by 3 × l - 1.[4] == 6.References == [1]Wujun,Zhaozhongming, Scale Co_occurrence Matrix for Texture Analysis Using Wavelet Transformation[J], Journal of Remote Sensing, Mar 2001, Volume 5,No.2, pp 100-103 [2]Duda R O. Pattern classification and scene analysis [M]. Wiley &Sons, Inc., 1973. [3]Kevin Lund, Curt Burgess, Producing high-dimensional semantic spaces from lexical co-occurrence, Behavior Research Methods, Instruments, & Computers June 1996, Volume 28, Issue 2, pp 203-208 [4] Mallat, S.G.: A theory for multiresolution signal decomposition: The wavelet representation. IEEE Transactions on Pattern Analysis and Machine Intelligence 11, 674–693 (1989) [5]Ahmad Fauzi, Mohammad Faizal, Optimal discrete wavelet frames features for texture-based image retrieval applications, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 5857. Date: 2009 Pages: 66-77. [6] Haralick R M. Statistical and structural approach to texture[J]. Proc. IEEE. 1979, 67: 786-804 == 7.External links: == [1]http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=738911&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D738911 [2] [http://www.mathworks.com/matlabcentral/fileexchange/11727-cooccurrence-matrix co-occurrence-matrix MATLAB tutorial] [3][http://www.mathworks.com/matlabcentral/fileexchange/11727-cooccurrence-matrix Co-occurrence Matrix]

Scale co-occurrence matrix: Difference between revisions