This physical phenomenon is related to a number of real world events, for example the popping noise from opening a Champaign bottle or the sound of a firecracker. Results from the current study enhance the understanding of the physics of an acoustic impulse, and represent a contribution to the...
The detected noise pixels are replaced with the output of a modified vector median filter over a spatially connected area. Simulation results in test color images show a superior performance of the proposed algorithms compared with the conventional vector median filter. The comparisons are made using...
,N}2, written as a column vector f∈RN, results from a zero-mean Gaussian noise b∈RN with a known standard deviation σ superimposed on an original image u0∈RN. The basic assumption of the K-SVD method is that each image patch (of fixed size n×n, and reformed as column vector ...
To remove random valued impulse noise from the digital images, a novel two step method has been proposed. The first step is to classify whether the center pixel in the 5 × 5 window is noisy or not, which is done using all neighbor directional weighted pixels in a 5 × 5 mask. The ...
Simulation results indicate that the proposed operator outperforms popular conventional as well as state-of-the-art impulse noise removal operators and offers superior performance in removing impulse noise from highly corrupted images while efficiently preserving image details and texture. 展开 ...
The second step is removing impulse noise with a median filter. The wavelet network presented here is a fixed one without learning. Experimental results show that our method acts on impulse noise effectively, and at the same time preserves chromaticity and image details very well. 展开 ...
removeimpulsenoisefromcorruptedimageswhilepreservingimagedetails.Itisefficient,andrequiresnoprevioustraining.Thealgorithmconsistsoftwosteps:impulsenoisedetectionandimpulsenoisecancellation.Extensiveexperimentalresultsshowthattheproposedapproachsignificantlyoutperformsmanyotherwell-knowntechniquesforimagenoiseremoval. 2006...
Where In represents the noisy image, I is the original (noise free) image and n is the additive noise on a pixel basis. Existing surveys of denoising techniques focus on edge and structure preservation and in the classification results of these denoising filters when applied in the spatial ...
and navigate to the /public/IR folder for the app, for example “StudioSixDigital”. In this folder, you will find .wav and .txt files for all Impulse Responses that you have done. The raw IR file will be named as “filenameWet.wav”, and the file with the data results in tab-de...
The filtered version is then subtracted from the main input signal. The goal of this algorithm is to remove the noise and leave the speech signal intact. Although the noise may never be completely removed, it is reduced significantly. The filter to perform this adaptive algorithm could be any...