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A DD_DTCWT Image De-noising Method Based on Scale Noise Level Estimation

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Advances in Image and Graphics Technologies (IGTA 2013)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 363))

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Abstract

In this paper, we propose a novel Scale Noise Level Estimation method based on Double-Density Dual Tree Complex Wavelet Transform (DD_DTCWT), which is referred to as DD_DTCWT_SNLE, to take the advantage of the correlation between the noise and noisy coefficients of DD_DTCWT. The novel DD_DTCWT_SNLE method is formulated through both theoretical analysis and numerical simulation, and is applied into three different threshold de-noising schemes respectively. Simulation results show that there is an approximate linear relation between DD_DTCWT_SNLE and the noise level and that DD_DTCWT_SNLE can reflect the noise level of coefficients in each layer more accurately. The proposed method outperforms the bivariate shrinkage algorithm and a gain of 0.8 dB in PSNR is obtained when compared to other DD_DTCWT based algorithms. We also show the universal applicability of our DD_DTCWT_SNLE for multi-scale linear operators, and its usage as a noise level estimator for all the other linear multi-scale decomposition coefficients.

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Author information

Authors and Affiliations

  1. Engineering College, Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, China

    Weiling Xu

  2. Dept. of Electronic Engineering, Nanjing College of Information Technology, Nanjing, 210046, China

    Shuwang Wang

Authors
  1. Weiling Xu
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  2. Shuwang Wang
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Editor information

Editors and Affiliations

  1. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Tieniu Tan

  2. Institute of Information Science, Beijing Jiaotong University, 100044, Beijing, China

    Qiuqi Ruan

  3. Institute of Computing Technology, Chinese Academy of Science, 100080, Beijing, China

    Xilin Chen

  4. Tsinghua University, Beijing, China

    Huimin Ma

  5. Chinese Academy of Sciences, Beijing, China

    Liang Wang

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© 2013 Springer-Verlag Berlin Heidelberg

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Xu, W., Wang, S. (2013). A DD_DTCWT Image De-noising Method Based on Scale Noise Level Estimation. In: Tan, T., Ruan, Q., Chen, X., Ma, H., Wang, L. (eds) Advances in Image and Graphics Technologies. IGTA 2013. Communications in Computer and Information Science, vol 363. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37149-3_18

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  • DOI: https://doi.org/10.1007/978-3-642-37149-3_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37148-6

  • Online ISBN: 978-3-642-37149-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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