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Image Denoising Based on Wavelet Transform Using Weighted Highpass Filtering Coefficient and Various Filters

shavya singh, Sarita Bhadauria

Abstract


Abstract— Image denoising (ID) is a material issue found in various image processing (IP) for preservation of image quality and information. There are numerous technique of denoising image. The most necessary property of ID model is that it should completely reduce noise as much as possible and edge preservation. Various algorithm has been developed in past but still it has scope for enhancement. This paper gives a insight view of some major work in the field of ID. Proposed algorithm is based on denoising of image using Discrete Wavelet Transform and then by adding Weighted Highpass Filter Coefficient in it. Thereafter denoised algorithm further enhanced by using various Filters(Mean filter, Median filter and Weiner filter) in order to achieve maximum PSNR and a lower value of MSE, RMSE. Experimental results show that the proposed algorithm with Median Filter improves the denoising performance and gives better visual quality. Peak signal to noise ratio(PSNR), Mean square error(MSE) and Root mean square error(RMSE) are used here as a performance parameter which measure the image quality.

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References


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DOI: https://doi.org/10.37628/ijtet.v3i2.538

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