Medical images such as computed tomography (CT) are degraded by different types of blur due to the imperfect resolution of the imaging system, data loss at the acquisition time and other technical reasons. The fastest way to deblur an image is by convolving a special kernel to the corrupted image. Laplacian kernels are famous and widely used in this field, but the issue is only few kernels are presented. This paper is trying to simulate the blur problem using various types of blur and attempt to restore the degraded images by using twenty novel kernels. Moreover, these kernels were tested with five types of blur that are: Average, Box, Gaussian, Pillbox and Atmospheric turbulence blur to determine which type of blur is suitable to be employed with kernels the most. The accuracy of the experimental results is measured with five diverse methods along with the success and the failure ratios. Finally, these kernels are applied to naturally degraded images obtained from different CT imaging systems.
보안공학연구지원센터(IJBSBT) [Science & Engineering Research Support Center, Republic of Korea(IJBSBT)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Bio-Science and Bio-Technology
간기
격월간
pISSN
2233-7849
수록기간
2009~2016
등재여부
SCOPUS
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Bio-Science and Bio-Technology Vol.4 No.3