Removing noise from the original signal is still a challenging problem for researchers. There have been several published algorithms and each approach has its assumptions, advantages, and limitations. This paper presents a review of some significant work in the area of image denoising. After a brief introduction, some popular approaches are classified into different groups and an overview of various algorithms and analysis is provided. Insights and potential future trends in the area of denoising are also discussed.

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. We study the application of a library of orthonormal bases to the reduction of correlated Gaussian noise. A joint condition on the library and the noise covariance is derived which ensures that simple thresholding in an adaptively chosen basis yields an estimation error within a logarithmic factor of the ideal risk. In the model example of a wavelet packet library and stationary noise the condition can be translated into a reverse Holder inequality on the power spectrum. 1. Introduction Consider signals given as vectors in R N , and assume that a finite library L of orthonormal bases is available. The total collection of w 2 B, B 2 L defines a dictionary D of M vectors. If L consists of only one basis, we have M = N . In general M NjLj where jLj is the number of bases in L. For the examples we have in mind, however, it holds that M NjLj. For wavelet packet libraries one has M = N(1 + log 2 N) while jLj ? 1:5 N , [CW]. Let a clean signal s be corrupted by additive noise z so t...

A translation-invariant denoising method, based on the Minimum Description Length (MDL) criterion and the Shift-Invariant Wavelet Packet Decomposition (SIWPD) is presented. A collection of signal models is generated using an extended library of orthonormal wavelet-packet bases, and an additive cost function, approximately representing the MDL principle, is derived. We show that the minimum description length of the noisy observed data is achieved by utilizing the SIWPD and thresholding the resulting coefficients. The signal estimator is combined with a modified Wigner distribution, yielding robust time-frequency representations, characterized by high resolution and suppressed interference-terms. The proposed method is compared with alternative approaches, and its superiority is demonstrated. 1. INTRODUCTION The use of wavelet bases for estimating noisy signals has been the object of considerable recent research. Traditional methods often entail noise removal by low-pass filtering, thu...

Abstract — Removal of noise from the original signal is still a bottleneck for researchers. There are several methods and techniques published and each method has its own advantages, disadvantages and assumptions. This paper presents a review of some significant work in the field of Image Denoising.The brief introduction of some popular approaches is provided and discussed. Insights and potential future trends are also discussed