Related papers: A simple denoising algorithm using wavelet transfo…

This work tackles the issue of noise removal from images, focusing on the well-known DCT image denoising algorithm. The latter, stemming from signal processing, has been well studied over the years. Though very simple, it is still used in…

This paper has been withdrawn because the content has been substantially improved in a later paper, arXiv:0806.1165.

This paper has been withdrawn by the author due to a crucial sign error.

In this paper we propose a method for wavelet denoising of signals contaminated with Gaussian noise when prior information about the $L^2$-energy of the signal is available. Assuming the independence model, according to which the wavelet…

This work proposes a learning-based statistical refinement method for improving the denoising results of a given denoiser without knowing the precise noise distribution or accessing clean images or calibration data. While there are many…

The paper is being withdrawn. A new submission will follow.

This paper has been withdrawn by the authors due to a gap in the proof of the main result (in 5.3).

Image denoising is a classic restoration problem. Yet, current deep learning methods are subject to the problems of generalization and interpretability. To mitigate these problems, in this project, we present a framework that is capable of…

Recent studies on learning-based image denoising have achieved promising performance on various noise reduction tasks. Most of these deep denoisers are trained either under the supervision of clean references, or unsupervised on synthetic…

This paper has been withdrawn by the author due to a crucial error in the submission action.

This paper has been withdrawn by the author due to a crucial error in the proof of Theorem 1.

This paper has been withdrawn by the author due to an error in section 7. There is a new version: arXiv:1011.3352.

This paper was withdrawn by the author. It turns out that similar ideas have been presented before. The author apologizes.

I discuss approaches to optimally remove noise from images. A generalization of Wiener filtering to Non-Gaussian distributions and wavelets is described, as well as an approach to measure the errors in the reconstructed images. We argue…

In this paper, we are interested in the classical problem of restoring data degraded by a convolution and the addition of a white Gaussian noise. The originality of the proposed approach is two-fold. Firstly, we formulate the restoration…

This paper has been withdrawn due to its publication

The paper has been withdrawn because the research work is still in progress.

Due to the potential risk of inducing cancers, radiation dose of X-ray CT should be reduced for routine patient scanning. However, in low-dose X-ray CT, severe artifacts usually occur due to photon starvation, beamhardening, etc, which…

A simple procedure to derive the transformation of a wavefunction under a change of reference frame is applied to some examples and its relation with the transformation of the Hamilton principal function is studied.

This paper has been withdrawn by the author(s), due to the existence of a much better paper in http://arxiv.org/abs/cs.CR/0207027