Effective noise removal technique for enhancement of the X-ray image / Azman Mohamed

Mohamed, Azman (2005) Effective noise removal technique for enhancement of the X-ray image / Azman Mohamed. Degree thesis, Universiti Teknologi MARA.

Abstract

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.

Metadata

Item Type: Thesis (Degree)
Creators:
Creators
Email / ID Num.
Mohamed, Azman
UNSPECIFIED
Subjects: Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science
Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > Database management
Q Science > QC Physics > Radiation physics (General) > X-rays
Divisions: Universiti Teknologi MARA, Shah Alam > Faculty of Computer and Mathematical Sciences
Programme: Bachelor of Science (Hons) Information System Engineering
Keywords: Noise, x-ray, image, removal technique
Date: April 2005
URI: https://ir.uitm.edu.my/id/eprint/9162
Edit Item
Edit Item

Download

[thumbnail of 9162.pdf] Text
9162.pdf

Download (56kB)

Digital Copy

Digital (fulltext) is available at:

Physical Copy

Physical status and holdings:
Item Status:

ID Number

9162

Indexing

Statistic

Statistic details