Image Denoising using DWT (Discrete Wavelet Transform) – Image Processing project- Matlab


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Image Denoising using DWT (Discrete Wavelet Transform) – Image Processing project- Matlab

Generally the Gaussian and salt Peppernoise occurred in images of different quality due torandom variation of pixel values. To denoise these images,it is necessary to apply various filtering techniques. So far there are lots of filtering methods proposed in literaturewhich includes the haar, sym4, and db4 WaveletTransform based soft and hard thresholding approach todenoise such type of noisy images.

This work analyse sexiting literature on haar, db4 and sym4 WaveletTransform for image denoising with variable size images from self generated grayscale database generated fromvarious image sources such as satellite images(NASA),Engineering Images and medical images.

However thisnew proposed Denoising method shows signs ofsatisfactory performances with respect to previousliterature on standard indices like Signal-to-Noise Ratio(SNR), Peak Signal to Noise Ratio (PSNR) and MeanSquare Error (MSE).

Literature indicates that Wavelet transform represents natural image better than any othertransformations. Therefore, Wavelet coeficient can be usedto improve quality of true image and from noise.

The aimof this work to eliminate the Gaussian and salt Peppernoise in wavelet transform domain. Subsequently a softand hard threshold based denoising algorithm has been developed.

Finally, the denoised image was compared withoriginal image using some quantifying statistical indicessuch as MSE, SNR and PSNR for different noise variance which the experimental results demonstrate its effectiveness over previous method.


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