Image denoising using Daubechies 4 Wavelet / Nik Norazira Nik Abd Rahman
This project focus on removing noises in the long bone x-ray images using Daubechies 4 Wavelet. Noise appears as unwanted dots, lines and smudges of color. It can be defined as random spaces speckles that exist in most of the digital images. The process of reducing the noise in the x-ray images was...
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2010
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Online Access: | https://ir.uitm.edu.my/id/eprint/63668/1/63668.pdf |
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my-uitm-ir.636682024-03-25T08:01:46Z Image denoising using Daubechies 4 Wavelet / Nik Norazira Nik Abd Rahman 2010 Nik Abd Rahman, Nik Norazira This project focus on removing noises in the long bone x-ray images using Daubechies 4 Wavelet. Noise appears as unwanted dots, lines and smudges of color. It can be defined as random spaces speckles that exist in most of the digital images. The process of reducing the noise in the x-ray images was done by decomposing the images into different frequency sub-bands and reconstructing the images into an image the less noise. The objectives of this project are to implement the Daubechies 4 wavelet transforms technique to remove noise in x-ray images and to evaluate the result of Daubechies 4 wavelet transforms technique using Peak Signal to Noise Ratio (PSNR). The scope of this project is the long x-ray images containing noises that are in JPG format. From the experimental results, it shows that Daubechies 4 Wavelet transform can be used to remove noise in the images through the decomposition and reconstruction process. In the future, this project needs enhancement to produce better result with implementing advance techniques. 2010 Thesis https://ir.uitm.edu.my/id/eprint/63668/ https://ir.uitm.edu.my/id/eprint/63668/1/63668.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty of Computer and Mathematical Sciences Mohamad Kamal, Nor Ashikin |
institution |
Universiti Teknologi MARA |
collection |
UiTM Institutional Repository |
language |
English |
advisor |
Mohamad Kamal, Nor Ashikin |
description |
This project focus on removing noises in the long bone x-ray images using Daubechies 4 Wavelet. Noise appears as unwanted dots, lines and smudges of color. It can be defined as random spaces speckles that exist in most of the digital images. The process of reducing the noise in the x-ray images was done by decomposing the images into different frequency sub-bands and reconstructing the images into an image the less noise. The objectives of this project are to implement the Daubechies 4 wavelet transforms technique to remove noise in x-ray images and to evaluate the result of Daubechies 4 wavelet transforms technique using Peak Signal to Noise Ratio (PSNR). The scope of this project is the long x-ray images containing noises that are in JPG format. From the experimental results, it shows that Daubechies 4 Wavelet transform can be used to remove noise in the images through the decomposition and reconstruction process. In the future, this project needs enhancement to produce better result with implementing advance techniques. |
format |
Thesis |
qualification_level |
Bachelor degree |
author |
Nik Abd Rahman, Nik Norazira |
spellingShingle |
Nik Abd Rahman, Nik Norazira Image denoising using Daubechies 4 Wavelet / Nik Norazira Nik Abd Rahman |
author_facet |
Nik Abd Rahman, Nik Norazira |
author_sort |
Nik Abd Rahman, Nik Norazira |
title |
Image denoising using Daubechies 4 Wavelet / Nik Norazira Nik Abd Rahman |
title_short |
Image denoising using Daubechies 4 Wavelet / Nik Norazira Nik Abd Rahman |
title_full |
Image denoising using Daubechies 4 Wavelet / Nik Norazira Nik Abd Rahman |
title_fullStr |
Image denoising using Daubechies 4 Wavelet / Nik Norazira Nik Abd Rahman |
title_full_unstemmed |
Image denoising using Daubechies 4 Wavelet / Nik Norazira Nik Abd Rahman |
title_sort |
image denoising using daubechies 4 wavelet / nik norazira nik abd rahman |
granting_institution |
Universiti Teknologi MARA (UiTM) |
granting_department |
Faculty of Computer and Mathematical Sciences |
publishDate |
2010 |
url |
https://ir.uitm.edu.my/id/eprint/63668/1/63668.pdf |
_version_ |
1804889653561524224 |