Type of Document	Dissertation
Author	Trifas, Alina Monica
Author's Email Address	mtrifas@hotmail.com
URN	etd-09282005-091721
Title	Medical Image Enhancement
Degree	Doctor of Philosophy (Ph.D.)
Department	Computer Science
Advisory Committee	Advisor Name Title John M. Tyler Committee Chair Bijaya B. Karki Committee Member Doris L. Carver Committee Member Jerry L. Trahan Committee Member Oleg S. Pianykh Committee Member Charles D. Bertolini Dean's Representative
Keywords	Fourier analysis filtering image enhancement multiscale contrast enhancement visual perception wavelet analysis
Date of Defense	2005-08-24
Availability	unrestricted
Abstract 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.
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