From multi-scale decomposition to non-multi-scale decomposition methods: a comprehensive survey of image fusion techniques and its applications
Image fusion is a well-recognized and a conventional field of image processing. Image
fusion provides an efficient way of enhancing and combining pixel-level data resulting in …
fusion provides an efficient way of enhancing and combining pixel-level data resulting in …
Image denoising using scale mixtures of Gaussians in the wavelet domain
We describe a method for removing noise from digital images, based on a statistical model
of the coefficients of an overcomplete multiscale oriented basis. Neighborhoods of …
of the coefficients of an overcomplete multiscale oriented basis. Neighborhoods of …
Bivariate shrinkage functions for wavelet-based denoising exploiting interscale dependency
L Sendur, IW Selesnick - IEEE Transactions on signal …, 2002 - ieeexplore.ieee.org
Most simple nonlinear thresholding rules for wavelet-based denoising assume that the
wavelet coefficients are independent. However, wavelet coefficients of natural images have …
wavelet coefficients are independent. However, wavelet coefficients of natural images have …
Bivariate shrinkage with local variance estimation
L Sendur, IW Selesnick - IEEE signal processing letters, 2002 - ieeexplore.ieee.org
The performance of image-denoising algorithms using wavelet transforms can be improved
significantly by taking into account the statistical dependencies among wavelet coefficients …
significantly by taking into account the statistical dependencies among wavelet coefficients …
On advances in statistical modeling of natural images
Statistical analysis of images reveals two interesting properties:(i) invariance of image
statistics to scaling of images, and (ii) non-Gaussian behavior of image statistics, ie high …
statistics to scaling of images, and (ii) non-Gaussian behavior of image statistics, ie high …
Multiresolution denoising for optical coherence tomography: a review and evaluation
A Pizurica, L Jovanov, B Huysmans… - Current Medical …, 2008 - ingentaconnect.com
Recently emerging non-invasive imaging modality-optical coherence tomography (OCT)-is
becoming an increasingly important diagnostic tool in various medical applications. One of …
becoming an increasingly important diagnostic tool in various medical applications. One of …
Estimating the probability of the presence of a signal of interest in multiresolution single-and multiband image denoising
A Pizurica, W Philips - IEEE Transactions on image processing, 2006 - ieeexplore.ieee.org
We develop three novel wavelet domain denoising methods for subband-adaptive, spatially-
adaptive and multivalued image denoising. The core of our approach is the estimation of the …
adaptive and multivalued image denoising. The core of our approach is the estimation of the …
Sparsity based denoising of spectral domain optical coherence tomography images
In this paper, we make contact with the field of compressive sensing and present a
development and generalization of tools and results for reconstructing irregularly sampled …
development and generalization of tools and results for reconstructing irregularly sampled …
[PDF][PDF] Speckle noise reduction in ultrasound images by wavelet thresholding based on weighted variance
In medical image processing, image denoising has become a very essential exercise all
through the diagnose. Arbitration between the perpetuation of useful diagnostic information …
through the diagnose. Arbitration between the perpetuation of useful diagnostic information …
Why simple shrinkage is still relevant for redundant representations?
M Elad - IEEE transactions on information theory, 2006 - ieeexplore.ieee.org
Shrinkage is a well known and appealing denoising technique, introduced originally by
Donoho and Johnstone in 1994. The use of shrinkage for denoising is known to be optimal …
Donoho and Johnstone in 1994. The use of shrinkage for denoising is known to be optimal …