TY - GEN
T1 - Combine EMD and ICA to learn image bases
AU - Fang, Dai
AU - Jianru, Xue
AU - Nanning, Zheng
PY - 2008
Y1 - 2008
N2 - A method of learning image bases from natural images is proposed in this paper. Natural image is decomposed into structure mode and non-structure mode by using Empirical Mode Decomposition (EMD) technique. The structure mode is made up of the first two Intrinsic Mode Functions (IMF) that represent the structure information of image. The other IMFs and residual image compose the non-structure mode. A structure bases dictionary or a non-structure bases dictionary is obtained by using Independent Component Analysis (ICA) on structure mode or nonstructure mode respectively. The image can be expressed by using the obtained dictionaries according to different attribution of image regions to implement image coding and sparse representation. Compared with ICA, the structure bases can better capture structure information of natural images, and the separation of the structure bases and non- structure bases can be profitable for the different description of different images information.
AB - A method of learning image bases from natural images is proposed in this paper. Natural image is decomposed into structure mode and non-structure mode by using Empirical Mode Decomposition (EMD) technique. The structure mode is made up of the first two Intrinsic Mode Functions (IMF) that represent the structure information of image. The other IMFs and residual image compose the non-structure mode. A structure bases dictionary or a non-structure bases dictionary is obtained by using Independent Component Analysis (ICA) on structure mode or nonstructure mode respectively. The image can be expressed by using the obtained dictionaries according to different attribution of image regions to implement image coding and sparse representation. Compared with ICA, the structure bases can better capture structure information of natural images, and the separation of the structure bases and non- structure bases can be profitable for the different description of different images information.
UR - https://www.scopus.com/pages/publications/52149084997
U2 - 10.1109/CISP.2008.606
DO - 10.1109/CISP.2008.606
M3 - 会议稿件
AN - SCOPUS:52149084997
SN - 9780769531199
T3 - Proceedings - 1st International Congress on Image and Signal Processing, CISP 2008
SP - 494
EP - 497
BT - Proceedings - 1st International Congress on Image and Signal Processing, CISP 2008
T2 - 1st International Congress on Image and Signal Processing, CISP 2008
Y2 - 27 May 2008 through 30 May 2008
ER -