Effective noise removal technique for enhancement of the X-ray image / Azman Mohamed
The noise removal is an important aspect of image processing, because the human visual System is very sensitive to the high amplitude of noise signals, thus noise in an image can result in a subjective loss of information. There are a lot of methods for noise removal like the Median, Mean, Gaussian...
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| 语言: | English |
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2005
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| 在线阅读: | https://ir.uitm.edu.my/id/eprint/9162/1/9162.pdf |
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my-uitm-ir.91622020-10-28T04:41:09Z Effective noise removal technique for enhancement of the X-ray image / Azman Mohamed 2005-04 Mohamed, Azman Electronic Computers. Computer Science Database management X-rays The noise removal is an important aspect of image processing, because the human visual System is very sensitive to the high amplitude of noise signals, thus noise in an image can result in a subjective loss of information. There are a lot of methods for noise removal like the Median, Mean, Gaussian or other filter. But there are only few measuring methods for the quality of a smoothed image. In most cases the developed filters are tested on standard images. On the other hand it is difficult to decide, which filter should be used for a given image with noise introduced to it. In this paper two methods for noise removal are introduced which are mean and median filtering in order examine important features for an automatic detection of adequate smoothing operators for a given noisy X-ray image. This paper tries to find the most suhable methods for noise removal and using the Signal-to-Noise Ratio to measure the noise. 2005-04 Thesis https://ir.uitm.edu.my/id/eprint/9162/ https://ir.uitm.edu.my/id/eprint/9162/1/9162.pdf text en public degree Universiti Teknologi MARA Perpustakaan Tun Abdul Razak |
| institution |
Universiti Teknologi MARA |
| collection |
UiTM Institutional Repository |
| language |
English |
| topic |
Electronic Computers Computer Science Database management X-rays |
| spellingShingle |
Electronic Computers Computer Science Database management X-rays Mohamed, Azman Effective noise removal technique for enhancement of the X-ray image / Azman Mohamed |
| description |
The noise removal is an important aspect of image processing, because the human visual System is very sensitive to the high amplitude of noise signals, thus noise in an image can result in a subjective loss of information. There are a lot of methods for noise removal like the Median, Mean, Gaussian or other filter. But there are only few measuring methods for the quality of a smoothed image. In most cases the developed filters are tested on standard images. On the other hand it is difficult to decide, which filter should be used for a given image with noise introduced to it. In this paper two methods for noise removal are introduced which are mean and
median filtering in order examine important features for an automatic detection of adequate smoothing operators for a given noisy X-ray image. This paper tries to find the
most suhable methods for noise removal and using the Signal-to-Noise Ratio to measure the noise. |
| format |
Thesis |
| qualification_level |
Bachelor degree |
| author |
Mohamed, Azman |
| author_facet |
Mohamed, Azman |
| author_sort |
Mohamed, Azman |
| title |
Effective noise removal technique for enhancement of the X-ray image / Azman Mohamed |
| title_short |
Effective noise removal technique for enhancement of the X-ray image / Azman Mohamed |
| title_full |
Effective noise removal technique for enhancement of the X-ray image / Azman Mohamed |
| title_fullStr |
Effective noise removal technique for enhancement of the X-ray image / Azman Mohamed |
| title_full_unstemmed |
Effective noise removal technique for enhancement of the X-ray image / Azman Mohamed |
| title_sort |
effective noise removal technique for enhancement of the x-ray image / azman mohamed |
| granting_institution |
Universiti Teknologi MARA |
| granting_department |
Perpustakaan Tun Abdul Razak |
| publishDate |
2005 |
| url |
https://ir.uitm.edu.my/id/eprint/9162/1/9162.pdf |
| _version_ |
1783733147797553152 |