YOU Xia, CHEN Fei, JIA Xiao-lin etc. Effects of dictionary scale on dictionary learning for DICOM image compression[J]. , 2015,30(6): 1045-1051 DOI: 10.3788/YJYXS20153006.1045.
Effects of dictionary scale on dictionary learning for DICOM image compression
With the accelerated developing of hospital digital medical
the amount of medical imaging data grows dramatically
which affects the data storage space and access speed. This paper proposes a new design which uses different scales dictionaries of MOD
K-SVD
ILS-DLA
RLS-DLA for digital imaging and communications in medicine (DICOM) image compression storage and restore methods based on dictionary learning. Compared with the traditional algorithms JPEG and JPEG2000
the proposed method has better performance
especially when the dictionary scale is smaller. For example
when the compression ratio is 20
using 44 dictionary scale
the peak signal to noise ratio (PSNR) of the proposed method is 7.8 dB higher than that of JPEG
and 1dB than JPEG2000.
关键词
Keywords
references
李萍.适用于PACS系统的医学图像压缩算法研究[D].郑州:郑州大学, 2013. Li P. The study of compression method for medical image in PACS[D]. Zhenzhou:Zhenzhou University, 2013. (in Chinese)
Engan K, Aase S, Husoy J. Method of optimal directions for frame design[C]. IEEE International Conference on Acoustics, Speech and Signal Processing, Phoneix, USA, 1999:2443-2446.
Aharon M, Elad M, Bruckstein A. K-SVD:An algorithm for designing overcomplete dictionaries for sparse representation[J]. IEEE Transactions on Signal Processing, 2006, 54:4311-4322.
Bryt O, Elad M. Compression of facial images using the K-SVD algorithm[J]. Journal of Visual Communication and Image Representation, 2008,19(4):270-282.
Skreting K, Engan K. Recursive least squares dictionary learning algorithm[J]. IEEE Transactions on Signal Processing, 2010,58(4):2121-2130.
Skreting K, Engan K. Image compression using learned dictionaries by RLS-DLA and compared with K-SVD[C]. IEEE International Conference on Acoustics, Speech and Signal Processing, Prague, Czech Republic, 2011:1517-1520.
霍承富.超光谱遥感图像压缩技术的研究[D].合肥:中国科技大学,2012. Huo C F. Research on hyperspectral remote sensing image compression technique[D]. Hefei:University of Science and Technology of China,2012. (in Chinese)
Mallat S, Zhang Z. Matching pursuits with time-frequency dictionaries[J]. IEEE Transactions on Signal Processing, 1993,41(12):3397-3415.
Pati Y, Rezaiifar R, Krislinaprasad P. Orthogonal matching pursuit:Recursive function approximation with applications to wavelet decomposition[C]. Proceedings of the 27th Annual Asilomar Conference on Signals, Sistems and Computers, Asilomar Grounds, 1993:40-44.
Gharavi-Alkhansari M, Huang T S. A fast orthogonal matching pursuit algorithm[C]. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Seattle, 1998:1389-1392.
Engan K, Skretting K, Husoy J H. A family of iterative LS-based dictionary learning algorithms, ILS-DLA, for sparse signal representation[J]. Digital Signal Process.,2007,17:32-49.
Mairal J, Bach F, Ponce J, et al. Online dictionary learning for sparse coding[C]. International Conference on Machine Learning, Montreal, Canada, 2009:689-696.
张健,李宏升.基于图论阈值算法的图像分割研究[J].液晶与显示, 2014,29(4):592-597. Zhang J, Li H S.Image mosaic research based on wavelet and rough set algorithm[J]. Chinese Journal of Liquid Crystals and Displays, 2014,29(4):592-597. (in Chinese)
石晓磊,王明泉. DICOM图像格式与BMP图像格式的转换[J].微计算机信息, 2010, 26:195-197. Shi X L, Wang M Q. Transformation of DICOMDigital Medical Image Format into BMP General Image Format[J]. Microcomputer Information, 2010, 26:195-197. (in Chinese)