Proceedings ArticleDOI
Poisson noise removal from images using the fast discrete Curvelet transform
Sandeep Palakkal,K.M.M. Prabhu +1 more
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TLDR
The results show that the VST combined with the FDCT is a promising candidate for Poisson denoising, and a simple approach to achieve this is presented.Abstract:
We propose a strategy to combine the variance stabilizing transform (VST), used for Poisson image denoising, with the fast discrete Curvelet transform (FDCT). The VST transforms the Poisson image to approximately Gaussian distributed, and the subsequent denoising can be performed in the Gaussian domain. However, the performance of the VST degrades when the original image intensity is very low. On the other hand, the FDCT can sparsely represent the intrinsic features of images having discontinuities along smooth curves. Therefore, it is suitable for denoising applications. Combining the VST with the FDCT leads to good Poisson image denoising algorithms, even for low intensity images. We present a simple approach to achieve this and demonstrate some simulation results. The results show that the VST combined with the FDCT is a promising candidate for Poisson denoising.read more
Citations
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Journal ArticleDOI
Poisson image denoising using fast discrete curvelet transform and wave atom
Sandeep Palakkal,K.M.M. Prabhu +1 more
TL;DR: The results demonstrate that the MS-VST combined with FDCT and WA are promising candidates for Poisson denoising, and a simple strategy to achieve this without increasing the computational complexity is proposed.
Book ChapterDOI
Poisson Noise Removal from Mammogram Using Poisson Unbiased Risk Estimation Technique
TL;DR: The recently developed denoising approach called the Poisson Unbiased Risk Estimation-Linear Expansion of Thresholds (PURE-LET) is implemented to improve the peak signal to noise ratio (PSNR) further and successfully removes Poisson noise better than the traditional mathematical transforms.
Journal Article
Poisson Noise Removal in Biomedical Imagesusing Non-Linear Techniques
Jisha J U,Sureshkumar +1 more
TL;DR: Two technique which combines Multi-Scale Variance Stabilizing Transform, Fast Discrete Curvelet Transform with Thresholding and MS-VST, FDCT with Null Hypothesis testing for effectively removing the Poisson Noise from the medical images are proposed.
Bilateral Filter Approach and Fast Discrete Curvelet Transform for Poisson Noise Removal from Images
Sajil Daniel John,Jilu George +1 more
TL;DR: Two methods of removing poisson noise from images using a bilateral filter and by Fast discrete Curvelet Transform (FDCT), which show that FDCT is more efficient for preserving image features, while bilateral filter is much faster and simple to implement.
Journal ArticleDOI
Removal of poisson noise in medical images using fdct integrated with rudin-osher-fatemi model
TL;DR: A novel approach for accomplishing Poisson noise removal in biomedical images by multiresolution representation where Fast Discrete Curvelet Transform is integrated with Rudin–Osher–Fatemi (ROF) model based on VST.
References
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Book ChapterDOI
The Hybrid Steepest Descent Method for the Variational Inequality Problem over the Intersection of Fixed Point Sets of Nonexpansive Mappings
TL;DR: The hybrid steepest descent (HST) method as mentioned in this paper is a simple algorithmic solution to the variational inequality problem defined over the nonempty intersection of multiple fixed point sets of nonexpansive mappings in a real Hilbert space.
Journal ArticleDOI
The Curvelet Transform
Jianwei Ma,Gerlind Plonka +1 more
TL;DR: A review on the curvelet transform, including its history beginning from wavelets, its logical relationship to other multiresolution multidirectional methods like contourlets and shearlets, and its basic theory and discrete algorithm is presented.
Journal ArticleDOI
Wavelets, Ridgelets, and Curvelets for Poisson Noise Removal
TL;DR: A variance stabilizing transform (VST) is applied on a filtered discrete Poisson process, yielding a near Gaussian process with asymptotic constant variance, leading to multiscale VSTs (MS-VSTs) and nonlinear decomposition schemes.
Multiscale Analysis of Photon-Limited Astronomical Images
TL;DR: Several multiscale approaches to photon-limited image reconstruction are reviewed, including wavelets combined with variance stabilizing transforms, corrected Haar wavelet transforms, multiplicative multiscales innovations, platelets, and the a trous wavelet transform.
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Poisson image denoising using fast discrete curvelet transform and wave atom
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