균일 척도를 이용한 적응 메디안필터의 구현 및 의료영상 응용
저자
발행사항
서울 : 建國大學校, 2003
학위논문사항
발행연도
2003
작성언어
한국어
주제어
KDC
559.99 판사항(4)
DDC
629.895 판사항(21)
발행국(도시)
서울
기타서명
Implementation of an adaptive median filter using homogeneous factor and its application to the medical images
형태사항
x, 155p. : 삽도 ; 26 cm
일반주기명
권말에 부록 수록
참고문헌 : p.107-113
소장기관
Generally analog images are easily corrupted by noise during the data transmission, capturing and processing. Small spot-like images which are known as quantum or scattering noise made X-ray image's resolution and quality poor, and this will degrade the usefulness of X-ray images as diagnostic tool. It is very urgent to develop processing techniques to improve image quality by reduction of noise. Up to present various filtering techniques such as mean filter, median filter, weighted median filter have been proposed and used for spatial noise reduction. Most of the filters had been focused on the reduction of impulse noise, in contrast to Gaussian noise and uniform noise had rarely been done.
In this study, the robust filters were proposed which could eliminate various noises using one algorithm under various circum-stances using digital image processing techniques. There might be possible to reduce the two kinds of noises simultaneously using single filter algorithm. Adaptive weighed median(AWM) filters based on local statistics was proposed and realized two kinds of the AWM filters. The one was a simple type of AWM filter whose weights are given by a simple non-linear function of three local characteristics. The other was the AWM filter which was constructed using homogeneous factor(HF). The noise added HF models which enabled the filter recognizing the local structures of the image were introduced, and algorithms to determine the HF for the detection systems with various inner statistical properties were developed. Noise reduction performances of existing nonlinear filter were compared on to the medical X-ray, ultrasonic, Lena and industrial X-ray images. Experimental results were summarized as follows.
1. On the X-ray images ;
First, the value of the homogeneous factor(HF) a of AWM filter effective greatly on image quality keeping ability as well as reduction of quantum noises and showed optimal at a=4.
Second, noise reduction index such as normal mean squared- error(NMSE) and peak signal to noise ratio(PSNR) was very effective measure to evaluate noise reduction performances. Proposed filter showed decrease in NMSE and increase in PSNR than conventional filters.
Based upon above experimental results it was proved when adopting AWM filter in a certain value of homogeneous factor, such as a=4, the original component of images were well kept and about 40% reduction rate increase than conventional filter could be achieved.
2. On the ultrasonic images homogeneous factor a=1.4 it was proved that the original component were well kept and 37% reduction rate increase than conventional filter could be achieved.
3. On the Lena images ;
First, mean values of mean-squared error were 0.175755 in random noise, 0.549082 in Gaussian noise and 1.185329 in homogeneous noise when applied only median filter(MF). It was proved that the nonlinear filter were still robust in impulse and Gaussian noise mixed environment. In addition to this edge detection characteristics were superior in sequentially when random, homogeneous and Gaussian noise added.
Second, in changing weighting value experiment on the weighting median filter(WMF), weighting value the slope were decreased linearly when eccentrically from the window center. Experimental results showed that steeper slope made filtering performance lessened so kept original image quality well. When the slope was slow the filter showed maximum performances.
Third, in comparison with adaptive median filter with weighted median filter when the slope was corresponded with homogeneous factor, in case of homogeneous factor a= 1.5 was optimum.
4. On the industrial X-ray images, homogeneous factor was effective in the reduction of noise and improvement of image resolution capability, in case of homogeneous factor a= 1.5 detection performance was very high.
It is revealed that proposed filter will be devoted to decrease in time for filtering by fast algorithm to compute slope of the adaptive median filter. In the future fuzzy weighted median filter(FWMF) capable of optimizing weighting value computation as well as noise power spectrum(NPS) on the evaluation of filter performance should be developed.
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