TY - GEN
T1 - S-transform based approach for texture analysis of medical images
AU - Pradhan, Pyari Mohan
AU - Cheng, Chun Hing
AU - Mitchell, Joseph Ross
PY - 2015/2/18
Y1 - 2015/2/18
N2 - Image texture is often characterized using gray level co-occurrence matrices (GLCM). The GLCM statistics reflect only the highest power and spatial frequencies. To address this, researchers have employed discrete wavelet transform (DWT) along with GLCM. However, this method involves a computationally complex convolution operation in the spatial domain, and also inherits the sampling limitations of the DWT. Extending texture analysis to the space-frequency (SF) domain will uncover patterns not visible through the GLCM-based approaches while still capitalizing on the effectiveness of the traditional co-occurrence matrix. The discrete S-transform (DST) provides the SF representation at a pixel by localizing with a Gaussian modulated sinusoidal window. The DST based texture analysis is proposed to improve upon the GLCM while providing advantages over wavelets. This paper presents the promising preliminary results achieved using the proposed method.
AB - Image texture is often characterized using gray level co-occurrence matrices (GLCM). The GLCM statistics reflect only the highest power and spatial frequencies. To address this, researchers have employed discrete wavelet transform (DWT) along with GLCM. However, this method involves a computationally complex convolution operation in the spatial domain, and also inherits the sampling limitations of the DWT. Extending texture analysis to the space-frequency (SF) domain will uncover patterns not visible through the GLCM-based approaches while still capitalizing on the effectiveness of the traditional co-occurrence matrix. The discrete S-transform (DST) provides the SF representation at a pixel by localizing with a Gaussian modulated sinusoidal window. The DST based texture analysis is proposed to improve upon the GLCM while providing advantages over wavelets. This paper presents the promising preliminary results achieved using the proposed method.
KW - Grey level co-occurrence matrix
KW - S-transform
KW - texture analysis
UR - http://www.scopus.com/inward/record.url?scp=84925428214&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84925428214&partnerID=8YFLogxK
U2 - 10.1109/ICHPCA.2014.7045374
DO - 10.1109/ICHPCA.2014.7045374
M3 - Conference contribution
T3 - 2014 International Conference on High Performance Computing and Applications, ICHPCA 2014
BT - 2014 International Conference on High Performance Computing and Applications, ICHPCA 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 International Conference on High Performance Computing and Applications, ICHPCA 2014
Y2 - 22 December 2014 through 24 December 2014
ER -