Journal of Systems Engineering and Electronics ›› 2013, Vol. 24 ›› Issue (1): 147-156.doi: 10.1109/JSEE.2013.00019

• SOFTWARE ALGORITHM AND SIMULATION • Previous Articles     Next Articles

Tunable-Q contourlet transform for image representation

Haijiang Wang1,2, Qinke Yang3,*, Rui Li1, and Zhihong Yao4   

  1. 1. Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling 712100, China;
    2. College of Urban and Environment Science, Shanxi Normal University, Linfen 041004, China;
    3. College of Urban and Environmental Sciences, Northwest University, Xi’an 710069, China;
    4. College of Resources and Environment, North China University of Water Resources and Electric Power, Zhengzhou 450011, China
  • Online:2013-02-25 Published:2010-01-03


A novel tunable-quality-factor (tunable-Q) contourlet transform for geometric image representation is proposed. The Laplacian pyramid in original contourlet decomposes a signal into channels that have the same bandwidth on a logarithmic scale, and is not suitable for images with different behavior in frequency domain. We employ a new tunable-Q decomposition defined in the frequency domain by which one can flexibly tune the bandwidth of decomposition channels. With an acceptable redundancy, this
tunable-Q contourlet is also anti-aliasing and its basis is sharply localized in the desired area of frequency and spatial domain. Our experiments in nonlinear approximation and denoising show that the contourlet using a better-suitable quality factor can achieve a more promising performance and often outperform wavelets and the previous contourlets both in visual quality and in terms of peak signal-to-noise ratio.