A New Combined Image Denoising Scheme for Mixed Noise Reduction


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Abstract


In number of image processing applications, image denoising plays an essential part as a preprocessing step. Since denoising introduces artifacts and causes blurring of image, image denoising still remains a challenging area for the researchers. In this paper, a combined method for reducing mixed noise from digital images has been proposed. The proposed method combines the advantages of spatial filtering such as Trilateral Filter and multiresolution techniques such as Wavelet Transform or Non Subsampled Contourlet Transform. The mixture of Gaussian noise and impulse noise can be powerfully decreased by the proposed scheme. In the transformed domain, Bayes Shrink is applied on the detail sub bands, while Trilateral Filter is applied as the pre filter and post filter. The performance is assessed in terms of Peak Signal to Noise Ratio (PSNR), Image Quality Index (IQI) and Edge Keeping Index (EKI). Experimental and comparison results proved that the proposed combined image denoising scheme outperforms the existing schemes in terms of the performance parameters and the visual quality.
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Keywords


Image Denoising; Trilateral Filter; Wavelet Transform; Non Sub Sampled Contourlet Transform; Image Quality Index

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