Journal of Korea Society of Digital Industry and Information Management (디지털산업정보학회논문지)

Korea Society of Digital Industry and Information Management (디지털산업정보학회)
권호 표지
DOI QR코드

DOI QR Code

Digital Image Processing Using Tunable Q-factor Discrete Wavelet Transformation

Q 인자의 조절이 가능한 이산 웨이브렛 변환을 이용한 디지털 영상처리

  • 신종홍 (숭실사이버대학교 융합정보보안학과)
  • Received : 2014.07.31
  • Accepted : 2014.08.20
  • Published : 2014.09.30
⟨ Previous Next ⟩

Abstract

This paper describes a 2D discrete-time wavelet transform for which the Q-factor is easily specified. Hence, the transform can be tuned according to the oscillatory behavior of the image signal to which it is applied. The tunable Q-factor wavelet transform (TQWT) is a fully-discrete wavelet transform for which the Q-factor, Q, of the underlying wavelet and the asymptotic redundancy (over-sampling rate), r, of the transform are easily and independently specified. In particular, the specified parameters Q and r can be real-valued. Therefore, by tuning Q, the oscillatory behavior of the wavelet can be chosen to match the oscillatory behavior of the signal of interest, so as to enhance the sparsity of a sparse signal representation. The TQWT is well suited to fast algorithms for sparsity-based inverse problems because it is a Parseval frame, easily invertible, and can be efficiently implemented. The TQWT can also be used as an easily-invertible discrete approximation of the continuous wavelet transform. The transform is based on a real valued scaling factor (dilation-factor) and is implemented using a perfect reconstruction over-sampled filter bank with real-valued sampling factors. The transform is parameterized by its Q-factor and its oversampling rate (redundancy), with modest oversampling rates (e. g. 3-4 times overcomplete) being sufficient for the analysis/synthesis functions to be well localized. Therefore, This method services good performance in image processing fields.

Keywords

References

  1. http://ko.wikipedia.org/
  2. I. W. Selesnick, "Sparse signal representations using the tunable Q-factor wavelet transform," In Proceedings of SPIE, Vol. 8138 (Wavelets and Sparsity XIV), 2011.
  3. 신종홍, "이중 밀도 웨이브렛 변환의 성능 향상을 위한 3방향 분리 처리 기법," 디지털산업정보학회 논문집, 제8권, 제2호, 2012, pp. 131-143.
  4. 신종홍, "3중 밀도 이산 웨이브렛 변환을 이용한 디지털 영상 처리 기법," 디지털산업정보학회논문집, 제8권, 제3호, 2012, pp. 131-143.
  5. I. W. Selesnick, "Wavelet transform with tunable Q-factor," IEEE Trans. on Signal Processing. Vol. 59, No. 8, 2011, pp. 3560-3575. https://doi.org/10.1109/TSP.2011.2143711
  6. Jingyu Yang, Yao Wang, "Image Coding Using DualTree Discrete Wavelet Transform," IEEE Trans. on Image Processing, Vol. 17, No. 9, 2008, pp. 1555-1569. https://doi.org/10.1109/TIP.2008.926159
  7. I. W. Selesnick, "A higher-density discrete wavelet transform," IEEE Trans. on Signal Processing, Vol. 54, No. 8, 2006, pp. 3039-3048. https://doi.org/10.1109/TSP.2006.875388
  8. 신종홍, "고밀도 이산 웨이브렛 변환을 이용한 2차원 디지털 영상 처리 기법," 한국인터넷방송통신학회논문지, 제13권, 제1호, 2013, pp. 1-8.