Bilateral signal variance estimation for wavelet-domain image denoising
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Summary
An adaptive approach is proposed that utilizes a bilateral statistical scheme adaptively adjusting the contributions of neighboring wavelet coefficients to provide an accurate estimation of the signal variance.
- Type
- article
- Published
- 2013-06-05
- Cited by
- 3
- References
- 13
- OpenAlex
- https://openalex.org/W2082559586
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:15680956
Keywords
Wavelet, Variance (accounting), SIGNAL (programming language), Mathematics, Mean squared error
References
- Image Denoising Using Wavelet Thresholding
- A wavelet-domain non-parametric statistical approach for image denoising
- Adaptive bidirectional diffusion for image restoration
- Low-complexity image denoising based on statistical modeling of wavelet coefficients
- Adapting to Unknown Smoothness via Wavelet Shrinkage
- Bilateral filtering for gray and color images
- Multiresolution Bilateral Filtering for Image Denoising
- AntShrink: Ant colony optimization for image shrinkage
- Image denoising algorithm via doubly local Wiener filtering with directional windows in wavelet domain
- A new method for removing mixed noises
- Bivariate shrinkage with local variance estimation
- Ideal spatial adaptation by wavelet shrinkage
- Spatially adaptive wavelet thresholding with context modeling for image denoising
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