Title :
Compressed sensing image processing based on nonsubsampled contourlet transform
Author :
Liu Fu ; Huang Caiyun
Author_Institution :
Coll. of Electr. & Inf. Eng., Hunan Int. Econ. Univ., Changsha, China
Abstract :
A compressed sensing algorithm based on nonsubsampled contourlet transform (NSCT) is proposed, NSCT can provide better sparsity than wavelet transform does in image transform. low-frequency coefficients of the image are preserved, only high-frequency coefficients are measured. In the reconstruction, OMP algorithm is used to recover high-frequency coefficients and the image is reconstructed by inverse nonsubsampled contourlet transform. Compared with wavelet compressed sensing algorithms, simulation results demonstrate that the quality of reconstructed image can be greatly improved under the same measurement number.
Keywords :
image processing; wavelet transforms; NSCT; compressed sensing image processing; high-frequency coefficients; image reconstruction; image transform; low-frequency coefficients; measurement number; nonsubsampled contourlet transform; wavelet compressed sensing algorithms; wavelet transform; Compressed sensing; Filter banks; Image coding; Image reconstruction; Signal processing algorithms; Wavelet transforms; compressed sensing; image processing; nonsubsampled contourlet transform;
Conference_Titel :
Systems and Informatics (ICSAI), 2012 International Conference on
Conference_Location :
Yantai
Print_ISBN :
978-1-4673-0198-5
DOI :
10.1109/ICSAI.2012.6223362