Medical image enhancement

Each image acquired from a medical imaging system is often part of a two-dimensional (2-D) image set whose total presents a three-dimensional (3-D) object for diagnosis. Unfortunately, sometimes these images are of poor quality. These distortions cause an inadequate object-of-interest presentation, which can result in inaccurate image analysis. Blurring is considered a serious problem. Therefore, “deblurring” an image to obtain better quality is an important issue in medical image processing. In our research, the image is initially decomposed. Contrast improvement is achieved by modifying the coefficients obtained from the decomposed image. Small coefficient values represent subtle details and are amplified to improve the visibility of the corresponding details. The stronger image density variations make a major contribution to the overall dynamic range, and have large coefficient values. These values can be reduced without much information loss.

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Computer Sciences

Grantor

Computer Science

Year dc:date.available

2005

Author dc:creator

• Trifas, Alina Monica

• Fourier analysis
• filtering
• image enhancement
• multiscale contrast enhancement
• visual perception
• wavelet analysis

Statement dc:rights

• unrestricted
• Release the entire work immediately for access worldwide.

Identifier

etd-09282005-091721
https://repository.lsu.edu/gradschool_dissertations/589

OAI identifier oai:identifier

oai:repository.lsu.edu:gradschool_dissertations-1588