In digital image different kinds of noises exist in an image and a variety of noise reduction techniques are available to perform de-noising. Selection of the de-noising algorithm depends on the types of noise. Gaussian noise, speckle noise, salt & pepper noise, shot noise are types of noises that are present in an image. The principle approach of image de-noising is filtering. Available filter...

There exist various image de-noising techniques. Amongst them orthogonal wavelet is preferred one. However, the orthogonal wavelet transform is not better technique as proper clustering of wavelet coefficients is not possible in this technique. So a better image de-noising technique is needed to have a better SNR and greater image information. In this work, image de-noising by linear minimum me...

A critical issue in the image restoration is the problem of de-noising images while keeping the integrity of relevant image information. A large number of image denoising techniques are proposed to remove noise. Mainly these techniques are depends upon the type of noise present in images. So image de-noising still remains a important challenge for researchers because de-noising techniques remov...

A method of single channel speech enhancement is proposed by de-noising using stationary wavelet transform. The approach developed herein processes multi-resolution wavelet coefficients individually and then recovery signal is reconstructed. The time invariant characteristics of stationary wavelet transform is particularly useful in speech de-noising. Experimental results show that the proposed...

The image de-noising naturally corrupted by noise is a classical problem in the field of signal or image processing. Additive random noise can easily be removed using simple threshold methods. De-noising of natural images corrupted by Gaussian noise using wavelet techniques are very effective because of its ability to capture the energy of a signal in few energy transform values. The wavelet de...

During the process of signal testing, it is often exposed to interference and influence of all kinds of noise signal, such as data collection and transmission and so noise may be introduced. So in practical applications, before analysis of the data measured, the need for de-noising processing. The signal denoising is a method for filtering the high frequency noise of the signal and makes the si...

IJSER © 2013 http://www.ijser.org Abstract — This paper presents the Wavelet based Image De-noising. The search for efficient image De-noising methods is still a valid challenge at the crossing of functional analysis and statistics using discrete wavelet transform. De-noising of stationary images corrupted by Gaussian noise using wavelet techniques is very effective because of its ability to ca...

In this paper, a discrete wavelet transform (DWT) based de-noising with its applications into the noise reduction for medical signal preprocessing is introduced. This work focuses on the hardware realization of a real-time wavelet de-noising procedure. The proposed de-noising circuit mainly consists of three modules: a DWT, a thresholding, and an inverse DWT (IDWT) modular circuits. We also pro...

in this paper, an optimal algorithm is presented for de-noising of medical images. the presented algorithm is based on improved version of local pixels grouping and principal component analysis. in local pixels grouping algorithm, blocks matching based on l2 norm method is utilized, which leads to matching performance improvement. to evaluate the performance of our proposed algorithm, peak sign...

In 1992 David Donoho has introduced the term de-noising. Despite its advantages, this method isn't used yet in communications. The goal of this paper is to adapt this method to the requirements of communications, especially for low SNR signals. Our contribution is a new threshold's value search method, that realizes the maximization of the signal to noise ratio at the output of the de-noising s...