Title :
Image compression using learned dictionaries by RLS-DLA and compared with K-SVD
Author :
Skretting, Karl ; Engan, Kjersti
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Univ. of Stavanger, Stavanger, Norway
Abstract :
The recently presented recursive least squares dictionary learning algorithm (RLS-DLA) is tested in a general image compression application. Dictionaries are learned in the pixel domain and in the 9/7 wavelet domain, and then tested in a straightforward compression scheme. Results are compared with state-of-the-art compression methods. The proposed compression scheme using RLS DLA learned dictionaries in the 9/7 wavelet domain per forms better than using dictionaries learned by other methods. The compression rate is just below the JPEG 2000 rate which is promising considering the simple entropy coding used.
Keywords :
data compression; dictionaries; image coding; learning (artificial intelligence); least squares approximations; singular value decomposition; wavelet transforms; 9/7 wavelet domain; K-SVD; RLS-DLA; dictionary learning algorithm; image compression; pixel domain; recursive least squares; straightforward compression scheme; Dictionaries; Discrete cosine transforms; Image coding; PSNR; Training; Transform coding; Wavelet domain; RLS-DLA; dictionary learning; image compression; overcomplete dictionary; sparse approximation;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on
Conference_Location :
Prague
Print_ISBN :
978-1-4577-0538-0
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2011.5946782