Thesis On Image Denoising

Thesis On Image Denoising-76
A very large portion of digital image processing is devoted to image denoising.

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This noise gets present amid acquisition, transmission, and storage processes.

Visual quality of the image is degraded due to the noise introduced in it.

There are a number of topics in digital image processing in which a student can go for deep research and can put forward a new theory.

Before going into thesis topics for image processing let us discuss the basics of digital image processing – what it is and why it is used.

BM3D is a state of the art technique, which gives better performance than all the other techniques studied here.

All the studied filters are applied on the color images.As BM3D outperforms all of the techniques studied here, our main focus is BM3D.BM3D is a transform domain filtering method which exploit the high correlation between the similar blocks in a natural image.have been studied in this work for suppression of AWGN.The recently developed Block matching and 3D filtering approach have also been performed efficiently under high variance of noise .Image restoration is the removal or reduction of degradations that are incurred while the image is being obtained.Degradation comes from blurring as well as noise due to electronic and photometric sources.The noise considered in this thesis is additive white Gaussian noise (AWGN).Some spatial-Domain filters like Mean filter, Median filter, Weighted median filter, Wiener filter etc.Performance of these filters are compared in terms of peak-signal-to-noise-ratio (PSNR), structural similarity index (SSIM).Results of ten different standard color images have been compared under varied noise levels.

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