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논문검색

Images Denoising and Enhancement Based on Dyadic Wavelet Domain Hidden Markov Models and Interpolation

초록

영어

For image denoising and enhancement, we combine dyadic wavelet transform and hidden Markov tree (HMT) model, and propose an image edge enhancement method based on dyadic wavelet domain hidden Markov models and interpolation algorithm. Making use of scale correlation between HMT model and binary wavelet coefficients, we establish different interpolation classification for different pixel distribution, realize enhanced image through transforming low resolution picture into high resolution picture, and simplify the complexity of computing at the same time. The simulation results show that compared with dyadic wavelet transform, both visual effects and quantitative analysis has significantly improved by wavelet domain HMT model method.

목차

Abstract
 1. Introduction
 2. Dyadic Wavelet Transform and Denoising Image
 3. Hidden Markov Tree Model
 4. Interpolation Calculation
 5. Images Denoising and Enhancement based on Wavelet Domain HMT Models
 6. Experiment
 7. Conclusions
 Acknowledgements
 References

저자정보

  • Zhenghong Huang Chongqing Key Laboratory of Electronic Commerce & Supply Chain System School of Computer Science and Technology, Chongqing Technology and Business University School of mathematics and statistics, Chongqing Technology and Business University, 19 Xuefu Avenue in Nan’an, Chongqing, 400067, China
  • Li Xia Chongqing Key Laboratory of Electronic Commerce & Supply Chain System School of Computer Science and Technology, Chongqing Technology and Business University School of mathematics and statistics, Chongqing Technology and Business University, 19 Xuefu Avenue in Nan’an, Chongqing, 400067, China

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