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doi:10.1016/S0031-3203(02)00350-3 
Copyright © 2003 Pattern Recognition Society. Published by Elsevier Science B.V.
Hybrid inter- and intra-wavelet scale image restoration
Received 15 February 2002;
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Abstract
This paper exploits both the inter- and intra-scale interdependencies that exist in wavelet coefficients to improve image restoration from noise-corrupted data. Using an over-complete wavelet expansion, we group the wavelet coefficients with the same spatial orientation at several scales. We then apply the linear minimum mean squared-error estimation to smooth noise. This scheme exploits the inter-scale correlation information of wavelet coefficients. To exploit the intra-scale dependencies, we calculate the co-variance matrix of each vector locally using a centered square-shaped window. Experiments show that the proposed hybrid scheme significantly outperforms methods exploiting only the intra- or inter-scale dependencies. The performance of noise removal also depends on wavelet filters. In our experiments a biorthogonal wavelet, which best characterizes the image inter-scale dependencies, achieves the best results.
Author Keywords: Image restoration; Overcomplete wavelet expansion; Inter- and intra-scale dependency; LMMSE
Article Outline
- 1. Introduction
- 2. Wavelet transform and overcomplete expansion
- 3. Hybrid intra- and inter-scale model and denoising algorithm
- 3.1. The LMMSE of wavelet coefficients
- 3.2. The intra-scale dependencies exploited model
- 3.3. The inter-scale dependencies exploited model
- 3.4. The intra- and inter-scale dependencies combined scheme
- 3.5. The LMMSE and thresholding hybrid algorithm
- 3.6. Wavelet bases selection
- 4. Experiments
- 5. Conclusion
- References
- Vitae
